SlideShare a Scribd company logo

Weekly #106: Deep Learning on Mobile

•
•
B
Bill Liu

https://learn.xnextcon.com/event/eventdetails/W20040610 This talk explains how to practically bring the power of convolutional neural networks and deep learning to memory and power-constrained devices like smartphones. You will learn various strategies to circumvent obstacles and build mobile-friendly shallow CNN architectures that significantly reduce the memory footprint and therefore make them easier to store on a smartphone; The talk also dives into how to use a family of model compression techniques to prune the network size for live image processing, enabling you to build a CNN version optimized for inference on mobile devices. Along the way, you will learn practical strategies to preprocess your data in a manner that makes the models more efficient in the real world.

Technology
1 of 76
Download to read offline
@PRACTICALDLBOOK@PRACTICALDLBOOK Deep Learning On Mobile A PRACTITIONER’S GUIDE
@PRACTICALDLBOOK 2
@PRACTICALDLBOOK@PRACTICALDLBOOK Deep Learning On Mobile A PRACTITIONER’S GUIDE
@PRACTICALDLBOOK @SiddhaGanju @MeherKasam @AnirudhKoul 4
@PRACTICALDLBOOK Why Deep Learning on Mobile? Privacy Reliability Cost Latency 5
@PRACTICALDLBOOK 6 https://media.giphy.com/media/fBzSGPMxD0isw/giphy.gif
@PRACTICALDLBOOK Latency Is Expensive! 7 100 milliseconds 1% loss [Amazon 2008]
@PRACTICALDLBOOK@PRACTICALDLBOOK Latency Is Expensive! 8 >3 sec load time 53% bounce Mobile Site Visits [Google Research, Webpagetest.org]
@PRACTICALDLBOOK@PRACTICALDLBOOK Power of 10 9 0.1s Seamless Uninterrupted flow of thought 1s 10s Limit of attention [Miller 1968; Card et al. 1991; Nielsen 1993]
@PRACTICALDLBOOK 10 Efficient Mobile Inference Engine Efficient Model+ = DL App
@PRACTICALDLBOOK How to Train My Model? 11
@PRACTICALDLBOOK 12 Learn to Play Melodica 3 Months
@PRACTICALDLBOOK Already Play Piano? 13
@PRACTICALDLBOOK 14 FINE-TUNE your skills 3months 1week
@PRACTICALDLBOOK@PRACTICALDLBOOK Fine-tuning 15 Assemble a dataset Find a pre- trained model Fine-tune a pre-trained model Run using existing frameworks “Don’t Be A Hero” - Andrej Karpathy
@PRACTICALDLBOOK@PRACTICALDLBOOK CustomVision.ai 16 Use Fatkun Browser Extension to download images from Search Engine, or use Bing Image Search API to programmatically download photos with proper rights
@PRACTICALDLBOOK 17
@PRACTICALDLBOOK 18
@PRACTICALDLBOOK Demo 19
@PRACTICALDLBOOK How Do I Run My Models? 20
@PRACTICALDLBOOK 21 Core ML TF Lite ML Kit
@PRACTICALDLBOOK@PRACTICALDLBOOK Apple Ecosystem 22 Metal • 2014 BNNS + MPS • 2016 Core ML • 2017 Core ML 2 • 2018 Core ML 3 • 2019 - Tiny models (~ KB)! - 1 bit model quantization support - Batch API for improved performance - Conversion support for MXNet, ONNX - tf-coreml
@PRACTICALDLBOOK@PRACTICALDLBOOK Apple Ecosystem 23 Metal • 2014 BNNS + MPS • 2016 Core ML • 2017 Core ML 2 • 2018 Core ML 3 • 2019 - On-device training - Personalization - Create ML UI
@PRACTICALDLBOOK Core ML Benchmark 538 129 75 557 109 7877 44 3674 35 3071 33 2926 18 15 0 100 200 300 400 500 600 ResNet-50 MobileNet SqueezeNet EXECUTION TIME (MS) ON APPLE DEVICES iPhone 5s (2013) iPhone 6 (2014) iPhone 6s (2015) iPhone 7 (2016) iPhone X (2017) iPhone XS (2018) 24 https://heartbeat.fritz.ai/ios-12-core-ml-benchmarks-b7a79811aac1 GPUs became a thing here!
@PRACTICALDLBOOK@PRACTICALDLBOOK TensorFlow Ecosystem 25 TensorFlow • 2015 TensorFlow Mobile • 2016 TensorFlow Lite • 2018 Smaller Faster Minimal dependencies Allows running custom operators
@PRACTICALDLBOOK@PRACTICALDLBOOK TensorFlow Lite is small 26 75KB Core Interpreter 1.5MB TensorFlow Mobile 400KB Core Interpreter + Supported Operations
@PRACTICALDLBOOK@PRACTICALDLBOOK TensorFlow Lite is Fast 27 Takes advantage of on-device hardware acceleration FlatBuffers •Reduces code footprint, memory usage •Reduces CPU cycles on serialization and deserialization •Improves startup time Pre-fused activations Combining batch normalization layer with previous Convolution Static memory and static execution plan Decreases load time
@PRACTICALDLBOOK@PRACTICALDLBOOK TensorFlow Ecosystem 28 TensorFlow • 2015 TensorFlow Mobile • 2016 TensorFlow Lite • 2018 Smaller Faster Minimal dependencies Allows running custom operators
@PRACTICALDLBOOK@PRACTICALDLBOOK TensorFlow Ecosystem 29 TensorFlow • 2015 TensorFlow Mobile • 2016 TensorFlow Lite • 2018 $ tflite_convert --keras_model_file = keras_model.h5 --output_file=foo.tflite
@PRACTICALDLBOOK@PRACTICALDLBOOK TensorFlow Ecosystem 30 TensorFlow • 2015 TensorFlow Mobile • 2016 TensorFlow Lite • 2018 Trained TensorFlow Model TF Lite Converter .tflite model Android App iOS App
@PRACTICALDLBOOK@PRACTICALDLBOOK ML Kit 31 Simple Abstraction over TensorFlow Lite Built in APIs for Image Labeling, OCR, Face Detection, Barcode scanning, Landmark detection, Smart reply Model management with Firebase Upload model on web interface to distribute A/B Testing
@PRACTICALDLBOOK 32 How Do I Keep My IP Safe?
@PRACTICALDLBOOK Fritz Full fledged mobile lifecycle support Deployment, instrumentation, etc. from Python 33
@PRACTICALDLBOOK@PRACTICALDLBOOK Recommendation for Product Development 34 Train a model using framework of choice Convert to TensorFlow Lite format Upload to Firebase Deploy to iOS/Android apps with MLKit
@PRACTICALDLBOOK@PRACTICALDLBOOK An Important Question 35 APP TOO BIG! WHAT DO? Apple does not allow apps over 200 MB to be downloaded over cellular network. Download on demand, and interpret on device instead.
@PRACTICALDLBOOK 36 What Effect Does Hardware have on Performance?
@PRACTICALDLBOOK Big Things Come In Small Packages 37
@PRACTICALDLBOOK Effect of Hardware L-R: iPhone XS, iPhone X, iPhone 5 38 https://twitter.com/matthieurouif/status/1126575118812110854?s=11
@PRACTICALDLBOOK TensorFlow Lite Benchmarks Alpha Lab releases Numericcal: http://alpha.lab.numericcal.com/
@PRACTICALDLBOOK 40 TensorFlow Lite Benchmarks Crowdsourcing AI Benchmark App by Andrey Ignatov from ETH Zurich. http://ai-benchmark.com/
@PRACTICALDLBOOK 41 Alchemy by Fritz https://alchemy.fritz.ai/ Python library to analyze and estimate mobile performance No need to deploy on mobile
@PRACTICALDLBOOK 42 User Experience Standpoint TO GET 95%+ USER COVERAGE, SUPPORT PHONES RELEASED IN THE PAST 3.5 YEARS IF NOT POSSIBLE, OFFER GRACEFUL DEGRADATION
@PRACTICALDLBOOK 43 Battery Standpoint Won’t AI inference kill the battery quickly? Answers: You don’t usually run AI models constantly, you run it for a few seconds. With a modern flagship phone, running Mobilenet at 30 fps should burn battery in 2-3 hours. Bigger question - Do you really need to run it at 30 FPS? Or could it be run 1 FPS?
@PRACTICALDLBOOK@PRACTICALDLBOOK Energy Reduction from 30 FPS to 1 FPS 44 iPad Pro 2017
@PRACTICALDLBOOK 45 What Exciting Applications Can I Build?
@PRACTICALDLBOOK Seeing AI Audible Barcode recognition Aim: Help blind users identify products using barcode Issue: Blind users don’t know where the barcode is Solution: Guide user in finding a barcode with audio cues 46
@PRACTICALDLBOOK AR Hand Puppets Hart Woolery from 2020CV Object Detection (Hand) + Key Point Estimation 47 [https://twitter.com/2020cv_inc/status/1093219359676280832] AR Hand Puppets, Hart Woolery from 2020CV, Object Detection (Hand) + Key Point Estimation
@PRACTICALDLBOOK 48 Zero-Gravity Space, Takahiro Horikawa, Mask RCNN (segmentation) + PixMix (Image In-Painting) + Unity (Physics)
@PRACTICALDLBOOK 49 [HomeCourt.ai]Object Detection (Ball, Hoop, Player) + Body Pose + Perspective Transformation
@PRACTICALDLBOOK 50 Polarr, Machine Guided Composition, Automated cropping with highest aesthetic score
@PRACTICALDLBOOK Remove objects Brian Schulman, Adventurous Co. Object Segmentation + Image In Painting 51 https://twitter.com/smashfactory/status/1139461813710442496
@PRACTICALDLBOOK Magic Sudoku App Edge Detection + Classification + AR Kit 52 https://twitter.com/braddwyer/status/910030265006923776
@PRACTICALDLBOOK People Segmentation AR Kit Abound Labs https://www.aboundlabs.com/ 53 https://twitter.com/nobbis/status/1135975245406515202
@PRACTICALDLBOOK@PRACTICALDLBOOK Snapchat 54 Face Swap GANs
@PRACTICALDLBOOK Can I Make My Model Even More Efficient? 55
@PRACTICALDLBOOK@PRACTICALDLBOOK How To Find Efficient Pre-Trained Models 56 Papers with Code https://paperswithcode.com/sota Model Zoo https://modelzoo.co
@PRACTICALDLBOOK@PRACTICALDLBOOK 57 What you can affordWhat you want
@PRACTICALDLBOOK Model Pruning Aim: Remove all connections with absolute weights below a threshold 58 Song Han, Jeff Pool, John Tran, William J. Dally, "Learning both Weights and Connections for Efficient Neural Networks", 2015
@PRACTICALDLBOOK Pruning in Keras model = tf.keras.models.Sequential([ tf.keras.layers.Flatten(), tf.keras.layers.Dense(512, activation=tf.nn.relu), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(10, activation=tf.nn.softmax) ]) 59 model = tf.keras.models.Sequential([ tf.keras.layers.Flatten(), prune.Prune(tf.keras.layers.Dense(512, activation=tf.nn.relu)), tf.keras.layers.Dropout(0.2), prune.Prune(tf.keras.layers.Dense(10, activation=tf.nn.softmax)) ])
@PRACTICALDLBOOK So many techniques - so little time! Quantization Weight sharing Channel pruning Filter pruning (ThiNet) Better Layers (Dilated Conv, HetConv, OctConv) Knowledge Distillation Binary networks (BNN, XNOR-Net) Lottery Ticket Hypothesis and many more ... 60
@PRACTICALDLBOOK 61 The one with the best thing ever
@PRACTICALDLBOOK Pocket Flow – 1 Line to Make a Model Efficient Tencent AI Labs created an Automatic Model Compression (AutoMC) framework 62
@PRACTICALDLBOOK 63 Can I design a better architecture myself? Maybe? But AI can do it much better!
@PRACTICALDLBOOK@PRACTICALDLBOOK AutoML – Let AI Design an Efficient Arch 64 Neural Architecture Search (NAS) - An automated approach for designing models using reinforcement learning while maximizing accuracy. Hardware Aware NAS = Maximizes accuracy while minimizing run-time on device Incorporates latency information into the reward objective function Measure real-world inference latency by executing on a particular platform 1.5x faster than MobileNetV2 (MnasNet) ResNet-50 accuracy with 19x less parameters SSD300 mAP with 35x less FLOPs
@PRACTICALDLBOOK 65 Evolution of Mobile NAS Methods Method Top-1 Acc (%) Pixel-1 Runtime Search Cost (GPU Hours) MobileNetV1 70.6 113 Manual MobileNetV2 72.0 75 Manual MnasNet 74.0 76 40,000 (4 years+) ProxylessNas-R 74.6 78 200 Single-Path NAS 74.9 79.5 3.75 hours
@PRACTICALDLBOOK ProxylessNAS – Per Hardware Tuned CNNs 66 Han Cai and Ligeng Zhu and Song Han, "ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware", ICLR 2019
@PRACTICALDLBOOK 67
@PRACTICALDLBOOK Can I Train on a Mobile Device? 68
@PRACTICALDLBOOK On-Device Training in Core ML 69 let updateTask = try MLUpdateTask( forModelAt: modelUrl, trainingData: trainingData, configuration: configuration, completionHandler: { [weak self] self.model = context.model context.model.write(to: newModelUrl) }) ⁻ Core ML 3 introduced on device learning ⁻ Never have to send training data to the server with the help of MLUpdateTask. ⁻ Schedule training when device is charging to save power
@PRACTICALDLBOOK Can I Train a Global Model Without Access to User Data? 70
@PRACTICALDLBOOK 71 FEDERATED LEARNING!!! https://federated.withgoogle.com/
@PRACTICALDLBOOK 72 TensorFlow Federated Train a global model using 1000s of devices without access to data Encryption + Secure Aggregation Protocol Can take a few days to wait for aggregations to build up https://github.com/tensorflow/federated
@PRACTICALDLBOOK What We Learnt Today 73 ⁻ Why deep learning on mobile? ⁻ Building a model ⁻ Running a model ⁻ Hardware factors ⁻ Benchmarking ⁻ State-of-the-art applications ⁻ Making a model more efficient ⁻ Federated Learning
@PRACTICALDLBOOK@PRACTICALDLBOOK How to Access the Slides in 1 Second HTTP://PRACTICALDL.AI @PRACTICALDLBOOK
@PRACTICALDLBOOK @SiddhaGanju @MeherKasam @AnirudhKoul 75
@PRACTICALDLBOOK

Recommended

Deep AutoViML For Tensorflow Models and MLOps Workflows
Deep AutoViML For Tensorflow Models and MLOps WorkflowsDeep AutoViML For Tensorflow Models and MLOps Workflows
Deep AutoViML For Tensorflow Models and MLOps WorkflowsBill Liu
 
Weekly #105: AutoViz and Auto_ViML Visualization and Machine Learning
Weekly #105: AutoViz and Auto_ViML Visualization and Machine LearningWeekly #105: AutoViz and Auto_ViML Visualization and Machine Learning
Weekly #105: AutoViz and Auto_ViML Visualization and Machine LearningBill Liu
 
AICamp - Dr Ramine Tinati - Making Computer Vision Real
AICamp - Dr Ramine Tinati - Making Computer Vision RealAICamp - Dr Ramine Tinati - Making Computer Vision Real
AICamp - Dr Ramine Tinati - Making Computer Vision RealRamine Tinati
 
Metaflow: The ML Infrastructure at Netflix
Metaflow: The ML Infrastructure at NetflixMetaflow: The ML Infrastructure at Netflix
Metaflow: The ML Infrastructure at NetflixBill Liu
 
AISF19 - Unleash Computer Vision at the Edge
AISF19 - Unleash Computer Vision at the EdgeAISF19 - Unleash Computer Vision at the Edge
AISF19 - Unleash Computer Vision at the EdgeBill Liu
 
Highly-scalable Reinforcement Learning RLlib for Real-world Applications
Highly-scalable Reinforcement Learning RLlib for Real-world ApplicationsHighly-scalable Reinforcement Learning RLlib for Real-world Applications
Highly-scalable Reinforcement Learning RLlib for Real-world ApplicationsBill Liu
 
Deploying ML models to production (frequently and safely) - PYCON 2018
Deploying ML models to production (frequently and safely) - PYCON 2018Deploying ML models to production (frequently and safely) - PYCON 2018
Deploying ML models to production (frequently and safely) - PYCON 2018David Tan
 
Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...
Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...
Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...Akash Tandon
 

Recommended

Deep AutoViML For Tensorflow Models and MLOps Workflows
Deep AutoViML For Tensorflow Models and MLOps WorkflowsDeep AutoViML For Tensorflow Models and MLOps Workflows
Deep AutoViML For Tensorflow Models and MLOps WorkflowsBill Liu
 
Weekly #105: AutoViz and Auto_ViML Visualization and Machine Learning
Weekly #105: AutoViz and Auto_ViML Visualization and Machine LearningWeekly #105: AutoViz and Auto_ViML Visualization and Machine Learning
Weekly #105: AutoViz and Auto_ViML Visualization and Machine LearningBill Liu
 
AICamp - Dr Ramine Tinati - Making Computer Vision Real
AICamp - Dr Ramine Tinati - Making Computer Vision RealAICamp - Dr Ramine Tinati - Making Computer Vision Real
AICamp - Dr Ramine Tinati - Making Computer Vision RealRamine Tinati
 
Metaflow: The ML Infrastructure at Netflix
Metaflow: The ML Infrastructure at NetflixMetaflow: The ML Infrastructure at Netflix
Metaflow: The ML Infrastructure at NetflixBill Liu
 
AISF19 - Unleash Computer Vision at the Edge
AISF19 - Unleash Computer Vision at the EdgeAISF19 - Unleash Computer Vision at the Edge
AISF19 - Unleash Computer Vision at the EdgeBill Liu
 
Highly-scalable Reinforcement Learning RLlib for Real-world Applications
Highly-scalable Reinforcement Learning RLlib for Real-world ApplicationsHighly-scalable Reinforcement Learning RLlib for Real-world Applications
Highly-scalable Reinforcement Learning RLlib for Real-world ApplicationsBill Liu
 
Deploying ML models to production (frequently and safely) - PYCON 2018
Deploying ML models to production (frequently and safely) - PYCON 2018Deploying ML models to production (frequently and safely) - PYCON 2018
Deploying ML models to production (frequently and safely) - PYCON 2018David Tan
 
Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...
Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...
Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...Akash Tandon
 
Automating machine learning lifecycle with kubeflow
Automating machine learning lifecycle with kubeflowAutomating machine learning lifecycle with kubeflow
Automating machine learning lifecycle with kubeflowStepan Pushkarev
 
Scaling up Deep Learning by Scaling Down
Scaling up Deep Learning by Scaling DownScaling up Deep Learning by Scaling Down
Scaling up Deep Learning by Scaling DownDatabricks
 
ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...
ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...
ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...Provectus
 
AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...
AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...
AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...Bill Liu
 
On-device machine learning: TensorFlow on Android
On-device machine learning: TensorFlow on AndroidOn-device machine learning: TensorFlow on Android
On-device machine learning: TensorFlow on AndroidYufeng Guo
 
TFX: A tensor flow-based production-scale machine learning platform
TFX: A tensor flow-based production-scale machine learning platformTFX: A tensor flow-based production-scale machine learning platform
TFX: A tensor flow-based production-scale machine learning platformShunya Ueta
 
Tensorflow Ecosystem
Tensorflow EcosystemTensorflow Ecosystem
Tensorflow EcosystemVivek Raja P S
 
Defend against adversarial AI using Adversarial Robustness Toolbox
Defend against adversarial AI using Adversarial Robustness Toolbox Defend against adversarial AI using Adversarial Robustness Toolbox
Defend against adversarial AI using Adversarial Robustness Toolbox Animesh Singh
 
An AI Based ATM Intelligent Security System using Open CV and YOLO
An AI Based ATM Intelligent Security System using Open CV and YOLOAn AI Based ATM Intelligent Security System using Open CV and YOLO
An AI Based ATM Intelligent Security System using Open CV and YOLOYogeshIJTSRD
 
Machine Learning In Production
Machine Learning In ProductionMachine Learning In Production
Machine Learning In ProductionSamir Bessalah
 
DeepLearning and Advanced Machine Learning on IoT
DeepLearning and Advanced Machine Learning on IoTDeepLearning and Advanced Machine Learning on IoT
DeepLearning and Advanced Machine Learning on IoTRomeo Kienzler
 
Managing and Versioning Machine Learning Models in Python
Managing and Versioning Machine Learning Models in PythonManaging and Versioning Machine Learning Models in Python
Managing and Versioning Machine Learning Models in PythonSimon Frid
 
Kubeflow Distributed Training and HPO
Kubeflow Distributed Training and HPOKubeflow Distributed Training and HPO
Kubeflow Distributed Training and HPOAnimesh Singh
 
10 more lessons learned from building Machine Learning systems
10 more lessons learned from building Machine Learning systems10 more lessons learned from building Machine Learning systems
10 more lessons learned from building Machine Learning systemsXavier Amatriain
 
TensorFlow 16: Building a Data Science Platform
TensorFlow 16: Building a Data Science Platform TensorFlow 16: Building a Data Science Platform
TensorFlow 16: Building a Data Science Platform Seldon
 
Hydrosphere.io for ODSC: Webinar on Kubeflow
Hydrosphere.io for ODSC: Webinar on KubeflowHydrosphere.io for ODSC: Webinar on Kubeflow
Hydrosphere.io for ODSC: Webinar on KubeflowRustem Zakiev
 
Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016
Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016
Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016MLconf
 
Model Drift Monitoring using Tensorflow Model Analysis
Model Drift Monitoring using Tensorflow Model AnalysisModel Drift Monitoring using Tensorflow Model Analysis
Model Drift Monitoring using Tensorflow Model AnalysisVivek Raja P S
 
Ml ops on AWS
Ml ops on AWSMl ops on AWS
Ml ops on AWSPhilipBasford
 
Advanced Model Inferencing leveraging Kubeflow Serving, KNative and Istio
Advanced Model Inferencing leveraging Kubeflow Serving, KNative and IstioAdvanced Model Inferencing leveraging Kubeflow Serving, KNative and Istio
Advanced Model Inferencing leveraging Kubeflow Serving, KNative and IstioAnimesh Singh
 
Siddha Ganju. Deep learning on mobile
Siddha Ganju. Deep learning on mobileSiddha Ganju. Deep learning on mobile
Siddha Ganju. Deep learning on mobileLviv Startup Club
 
Siddha Ganju, NVIDIA. Deep Learning for Mobile
Siddha Ganju, NVIDIA. Deep Learning for MobileSiddha Ganju, NVIDIA. Deep Learning for Mobile
Siddha Ganju, NVIDIA. Deep Learning for MobileIT Arena
 

More Related Content

What's hot

Automating machine learning lifecycle with kubeflow
Automating machine learning lifecycle with kubeflowAutomating machine learning lifecycle with kubeflow
Automating machine learning lifecycle with kubeflowStepan Pushkarev
 
Scaling up Deep Learning by Scaling Down
Scaling up Deep Learning by Scaling DownScaling up Deep Learning by Scaling Down
Scaling up Deep Learning by Scaling DownDatabricks
 
ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...
ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...
ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...Provectus
 
AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...
AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...
AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...Bill Liu
 
On-device machine learning: TensorFlow on Android
On-device machine learning: TensorFlow on AndroidOn-device machine learning: TensorFlow on Android
On-device machine learning: TensorFlow on AndroidYufeng Guo
 
TFX: A tensor flow-based production-scale machine learning platform
TFX: A tensor flow-based production-scale machine learning platformTFX: A tensor flow-based production-scale machine learning platform
TFX: A tensor flow-based production-scale machine learning platformShunya Ueta
 
Defend against adversarial AI using Adversarial Robustness Toolbox
Defend against adversarial AI using Adversarial Robustness Toolbox Defend against adversarial AI using Adversarial Robustness Toolbox
Defend against adversarial AI using Adversarial Robustness Toolbox Animesh Singh
 
An AI Based ATM Intelligent Security System using Open CV and YOLO
An AI Based ATM Intelligent Security System using Open CV and YOLOAn AI Based ATM Intelligent Security System using Open CV and YOLO
An AI Based ATM Intelligent Security System using Open CV and YOLOYogeshIJTSRD
 
Machine Learning In Production
Machine Learning In ProductionMachine Learning In Production
Machine Learning In ProductionSamir Bessalah
 
DeepLearning and Advanced Machine Learning on IoT
DeepLearning and Advanced Machine Learning on IoTDeepLearning and Advanced Machine Learning on IoT
DeepLearning and Advanced Machine Learning on IoTRomeo Kienzler
 
Managing and Versioning Machine Learning Models in Python
Managing and Versioning Machine Learning Models in PythonManaging and Versioning Machine Learning Models in Python
Managing and Versioning Machine Learning Models in PythonSimon Frid
 
Kubeflow Distributed Training and HPO
Kubeflow Distributed Training and HPOKubeflow Distributed Training and HPO
Kubeflow Distributed Training and HPOAnimesh Singh
 
10 more lessons learned from building Machine Learning systems
10 more lessons learned from building Machine Learning systems10 more lessons learned from building Machine Learning systems
10 more lessons learned from building Machine Learning systemsXavier Amatriain
 
TensorFlow 16: Building a Data Science Platform
TensorFlow 16: Building a Data Science Platform TensorFlow 16: Building a Data Science Platform
TensorFlow 16: Building a Data Science Platform Seldon
 
Hydrosphere.io for ODSC: Webinar on Kubeflow
Hydrosphere.io for ODSC: Webinar on KubeflowHydrosphere.io for ODSC: Webinar on Kubeflow
Hydrosphere.io for ODSC: Webinar on KubeflowRustem Zakiev
 
Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016
Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016
Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016MLconf
 
Model Drift Monitoring using Tensorflow Model Analysis
Model Drift Monitoring using Tensorflow Model AnalysisModel Drift Monitoring using Tensorflow Model Analysis
Model Drift Monitoring using Tensorflow Model AnalysisVivek Raja P S
 
Advanced Model Inferencing leveraging Kubeflow Serving, KNative and Istio
Advanced Model Inferencing leveraging Kubeflow Serving, KNative and IstioAdvanced Model Inferencing leveraging Kubeflow Serving, KNative and Istio
Advanced Model Inferencing leveraging Kubeflow Serving, KNative and IstioAnimesh Singh
 

What's hot (20)

Automating machine learning lifecycle with kubeflow
Automating machine learning lifecycle with kubeflowAutomating machine learning lifecycle with kubeflow
Automating machine learning lifecycle with kubeflow
 
Scaling up Deep Learning by Scaling Down
Scaling up Deep Learning by Scaling DownScaling up Deep Learning by Scaling Down
Scaling up Deep Learning by Scaling Down
 
ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...
ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...
ODSC webinar "Kubeflow, MLFlow and Beyond — augmenting ML delivery" Stepan Pu...
 
AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...
AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...
AISF19 - Building Scalable, Kubernetes-Native ML/AI Pipelines with TFX, KubeF...
 
On-device machine learning: TensorFlow on Android
On-device machine learning: TensorFlow on AndroidOn-device machine learning: TensorFlow on Android
On-device machine learning: TensorFlow on Android
 
TFX: A tensor flow-based production-scale machine learning platform
TFX: A tensor flow-based production-scale machine learning platformTFX: A tensor flow-based production-scale machine learning platform
TFX: A tensor flow-based production-scale machine learning platform
 
Tensorflow Ecosystem
Tensorflow EcosystemTensorflow Ecosystem
Tensorflow Ecosystem
 
Defend against adversarial AI using Adversarial Robustness Toolbox
Defend against adversarial AI using Adversarial Robustness Toolbox Defend against adversarial AI using Adversarial Robustness Toolbox
Defend against adversarial AI using Adversarial Robustness Toolbox
 
An AI Based ATM Intelligent Security System using Open CV and YOLO
An AI Based ATM Intelligent Security System using Open CV and YOLOAn AI Based ATM Intelligent Security System using Open CV and YOLO
An AI Based ATM Intelligent Security System using Open CV and YOLO
 
Machine Learning In Production
Machine Learning In ProductionMachine Learning In Production
Machine Learning In Production
 
DeepLearning and Advanced Machine Learning on IoT
DeepLearning and Advanced Machine Learning on IoTDeepLearning and Advanced Machine Learning on IoT
DeepLearning and Advanced Machine Learning on IoT
 
Managing and Versioning Machine Learning Models in Python
Managing and Versioning Machine Learning Models in PythonManaging and Versioning Machine Learning Models in Python
Managing and Versioning Machine Learning Models in Python
 
Kubeflow Distributed Training and HPO
Kubeflow Distributed Training and HPOKubeflow Distributed Training and HPO
Kubeflow Distributed Training and HPO
 
10 more lessons learned from building Machine Learning systems
10 more lessons learned from building Machine Learning systems10 more lessons learned from building Machine Learning systems
10 more lessons learned from building Machine Learning systems
 
TensorFlow 16: Building a Data Science Platform
TensorFlow 16: Building a Data Science Platform TensorFlow 16: Building a Data Science Platform
TensorFlow 16: Building a Data Science Platform
 
Hydrosphere.io for ODSC: Webinar on Kubeflow
Hydrosphere.io for ODSC: Webinar on KubeflowHydrosphere.io for ODSC: Webinar on Kubeflow
Hydrosphere.io for ODSC: Webinar on Kubeflow
 
Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016
Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016
Nikhil Garg, Engineering Manager, Quora at MLconf SF 2016
 
Model Drift Monitoring using Tensorflow Model Analysis
Model Drift Monitoring using Tensorflow Model AnalysisModel Drift Monitoring using Tensorflow Model Analysis
Model Drift Monitoring using Tensorflow Model Analysis
 
Ml ops on AWS
Ml ops on AWSMl ops on AWS
Ml ops on AWS
 
Advanced Model Inferencing leveraging Kubeflow Serving, KNative and Istio
Advanced Model Inferencing leveraging Kubeflow Serving, KNative and IstioAdvanced Model Inferencing leveraging Kubeflow Serving, KNative and Istio
Advanced Model Inferencing leveraging Kubeflow Serving, KNative and Istio
 

Similar to Weekly #106: Deep Learning on Mobile

Siddha Ganju. Deep learning on mobile
Siddha Ganju. Deep learning on mobileSiddha Ganju. Deep learning on mobile
Siddha Ganju. Deep learning on mobileLviv Startup Club
 
Siddha Ganju, NVIDIA. Deep Learning for Mobile
Siddha Ganju, NVIDIA. Deep Learning for MobileSiddha Ganju, NVIDIA. Deep Learning for Mobile
Siddha Ganju, NVIDIA. Deep Learning for MobileIT Arena
 
Dog Breed Classification using PyTorch on Azure Machine Learning
Dog Breed Classification using PyTorch on Azure Machine LearningDog Breed Classification using PyTorch on Azure Machine Learning
Dog Breed Classification using PyTorch on Azure Machine LearningHeather Spetalnick
 
Data science lab enabling flexibility
Data science lab enabling flexibilityData science lab enabling flexibility
Data science lab enabling flexibilityKognitio
 
And Then There Are Algorithms
And Then There Are AlgorithmsAnd Then There Are Algorithms
And Then There Are AlgorithmsInfluxData
 
Kusto (Azure Data Explorer) Training for R&D - January 2019
Kusto (Azure Data Explorer) Training for R&D - January 2019 Kusto (Azure Data Explorer) Training for R&D - January 2019
Kusto (Azure Data Explorer) Training for R&D - January 2019 Tal Bar-Zvi
 
Deep learning for Industries
Deep learning for IndustriesDeep learning for Industries
Deep learning for IndustriesRahul Kumar
 
Scaling Face Recognition with Big Data
Scaling Face Recognition with Big DataScaling Face Recognition with Big Data
Scaling Face Recognition with Big DataBogdan Bocse
 
ML in the Browser: Interactive Experiences with Tensorflow.js
ML in the Browser: Interactive Experiences with Tensorflow.jsML in the Browser: Interactive Experiences with Tensorflow.js
ML in the Browser: Interactive Experiences with Tensorflow.jsC4Media
 
Automated ML Workflow for Distributed Big Data Using Analytics Zoo (CVPR2020 ...
Automated ML Workflow for Distributed Big Data Using Analytics Zoo (CVPR2020 ...Automated ML Workflow for Distributed Big Data Using Analytics Zoo (CVPR2020 ...
Automated ML Workflow for Distributed Big Data Using Analytics Zoo (CVPR2020 ...Jason Dai
 
Going deep (learning) with tensor flow and quarkus
Going deep (learning) with tensor flow and quarkusGoing deep (learning) with tensor flow and quarkus
Going deep (learning) with tensor flow and quarkusRed Hat Developers
 
Real Time Processing Using Twitter Heron by Karthik Ramasamy
Real Time Processing Using Twitter Heron by Karthik RamasamyReal Time Processing Using Twitter Heron by Karthik Ramasamy
Real Time Processing Using Twitter Heron by Karthik RamasamyData Con LA
 
JAX London 22: Debugging Microservices "Remocally" in Kubernetes with Telepre...
JAX London 22: Debugging Microservices "Remocally" in Kubernetes with Telepre...JAX London 22: Debugging Microservices "Remocally" in Kubernetes with Telepre...
JAX London 22: Debugging Microservices "Remocally" in Kubernetes with Telepre...Daniel Bryant
 
BISSA: Empowering Web gadget Communication with Tuple Spaces
BISSA: Empowering Web gadget Communication with Tuple SpacesBISSA: Empowering Web gadget Communication with Tuple Spaces
BISSA: Empowering Web gadget Communication with Tuple SpacesSrinath Perera
 
Need to-know patterns building microservices - java one
Need to-know patterns building microservices - java oneNeed to-know patterns building microservices - java one
Need to-know patterns building microservices - java oneVincent Kok
 
Multiplatform Spark solution for Graph datasources by Javier Dominguez
Multiplatform Spark solution for Graph datasources by Javier DominguezMultiplatform Spark solution for Graph datasources by Javier Dominguez
Multiplatform Spark solution for Graph datasources by Javier DominguezBig Data Spain
 
Deep learning on mobile
Deep learning on mobileDeep learning on mobile
Deep learning on mobileAnirudh Koul
 

Similar to Weekly #106: Deep Learning on Mobile (20)

Siddha Ganju. Deep learning on mobile
Siddha Ganju. Deep learning on mobileSiddha Ganju. Deep learning on mobile
Siddha Ganju. Deep learning on mobile
 
Siddha Ganju, NVIDIA. Deep Learning for Mobile
Siddha Ganju, NVIDIA. Deep Learning for MobileSiddha Ganju, NVIDIA. Deep Learning for Mobile
Siddha Ganju, NVIDIA. Deep Learning for Mobile
 
Dog Breed Classification using PyTorch on Azure Machine Learning
Dog Breed Classification using PyTorch on Azure Machine LearningDog Breed Classification using PyTorch on Azure Machine Learning
Dog Breed Classification using PyTorch on Azure Machine Learning
 
General Learning.pptx
General Learning.pptxGeneral Learning.pptx
General Learning.pptx
 
Data science lab enabling flexibility
Data science lab enabling flexibilityData science lab enabling flexibility
Data science lab enabling flexibility
 
And Then There Are Algorithms
And Then There Are AlgorithmsAnd Then There Are Algorithms
And Then There Are Algorithms
 
Kusto (Azure Data Explorer) Training for R&D - January 2019
Kusto (Azure Data Explorer) Training for R&D - January 2019 Kusto (Azure Data Explorer) Training for R&D - January 2019
Kusto (Azure Data Explorer) Training for R&D - January 2019
 
Deep learning for Industries
Deep learning for IndustriesDeep learning for Industries
Deep learning for Industries
 
Scaling Face Recognition with Big Data
Scaling Face Recognition with Big DataScaling Face Recognition with Big Data
Scaling Face Recognition with Big Data
 
Trends in DNN compression
Trends in DNN compressionTrends in DNN compression
Trends in DNN compression
 
ML in the Browser: Interactive Experiences with Tensorflow.js
ML in the Browser: Interactive Experiences with Tensorflow.jsML in the Browser: Interactive Experiences with Tensorflow.js
ML in the Browser: Interactive Experiences with Tensorflow.js
 
Automated ML Workflow for Distributed Big Data Using Analytics Zoo (CVPR2020 ...
Automated ML Workflow for Distributed Big Data Using Analytics Zoo (CVPR2020 ...Automated ML Workflow for Distributed Big Data Using Analytics Zoo (CVPR2020 ...
Automated ML Workflow for Distributed Big Data Using Analytics Zoo (CVPR2020 ...
 
Going deep (learning) with tensor flow and quarkus
Going deep (learning) with tensor flow and quarkusGoing deep (learning) with tensor flow and quarkus
Going deep (learning) with tensor flow and quarkus
 
Real Time Processing Using Twitter Heron by Karthik Ramasamy
Real Time Processing Using Twitter Heron by Karthik RamasamyReal Time Processing Using Twitter Heron by Karthik Ramasamy
Real Time Processing Using Twitter Heron by Karthik Ramasamy
 
JAX London 22: Debugging Microservices "Remocally" in Kubernetes with Telepre...
JAX London 22: Debugging Microservices "Remocally" in Kubernetes with Telepre...JAX London 22: Debugging Microservices "Remocally" in Kubernetes with Telepre...
JAX London 22: Debugging Microservices "Remocally" in Kubernetes with Telepre...
 
BISSA: Empowering Web gadget Communication with Tuple Spaces
BISSA: Empowering Web gadget Communication with Tuple SpacesBISSA: Empowering Web gadget Communication with Tuple Spaces
BISSA: Empowering Web gadget Communication with Tuple Spaces
 
Need to-know patterns building microservices - java one
Need to-know patterns building microservices - java oneNeed to-know patterns building microservices - java one
Need to-know patterns building microservices - java one
 
Multiplatform Spark solution for Graph datasources by Javier Dominguez
Multiplatform Spark solution for Graph datasources by Javier DominguezMultiplatform Spark solution for Graph datasources by Javier Dominguez
Multiplatform Spark solution for Graph datasources by Javier Dominguez
 
Microsoft Dryad
Microsoft DryadMicrosoft Dryad
Microsoft Dryad
 
Deep learning on mobile
Deep learning on mobileDeep learning on mobile
Deep learning on mobile
 

More from Bill Liu

Walk Through a Real World ML Production Project
Walk Through a Real World ML Production ProjectWalk Through a Real World ML Production Project
Walk Through a Real World ML Production ProjectBill Liu
 
Redefining MLOps with Model Deployment, Management and Observability in Produ...
Redefining MLOps with Model Deployment, Management and Observability in Produ...Redefining MLOps with Model Deployment, Management and Observability in Produ...
Redefining MLOps with Model Deployment, Management and Observability in Produ...Bill Liu
 
Productizing Machine Learning at the Edge
Productizing Machine Learning at the EdgeProductizing Machine Learning at the Edge
Productizing Machine Learning at the EdgeBill Liu
 
Transformers in Vision: From Zero to Hero
Transformers in Vision: From Zero to HeroTransformers in Vision: From Zero to Hero
Transformers in Vision: From Zero to HeroBill Liu
 
Practical Crowdsourcing for ML at Scale
Practical Crowdsourcing for ML at ScalePractical Crowdsourcing for ML at Scale
Practical Crowdsourcing for ML at ScaleBill Liu
 
Building large scale transactional data lake using apache hudi
Building large scale transactional data lake using apache hudiBuilding large scale transactional data lake using apache hudi
Building large scale transactional data lake using apache hudiBill Liu
 
Deep Reinforcement Learning and Its Applications
Deep Reinforcement Learning and Its ApplicationsDeep Reinforcement Learning and Its Applications
Deep Reinforcement Learning and Its ApplicationsBill Liu
 
Big Data and AI in Fighting Against COVID-19
Big Data and AI in Fighting Against COVID-19Big Data and AI in Fighting Against COVID-19
Big Data and AI in Fighting Against COVID-19Bill Liu
 
Build computer vision models to perform object detection and classification w...
Build computer vision models to perform object detection and classification w...Build computer vision models to perform object detection and classification w...
Build computer vision models to perform object detection and classification w...Bill Liu
 
Causal Inference in Data Science and Machine Learning
Causal Inference in Data Science and Machine LearningCausal Inference in Data Science and Machine Learning
Causal Inference in Data Science and Machine LearningBill Liu
 
AISF19 - On Blending Machine Learning with Microeconomics
AISF19 - On Blending Machine Learning with MicroeconomicsAISF19 - On Blending Machine Learning with Microeconomics
AISF19 - On Blending Machine Learning with MicroeconomicsBill Liu
 
AISF19 - Travel in the AI-First World
AISF19 - Travel in the AI-First WorldAISF19 - Travel in the AI-First World
AISF19 - Travel in the AI-First WorldBill Liu
 
Toronto meetup 20190917
Toronto meetup 20190917Toronto meetup 20190917
Toronto meetup 20190917Bill Liu
 
Feature Engineering for NLP
Feature Engineering for NLPFeature Engineering for NLP
Feature Engineering for NLPBill Liu
 
Auto visualization and viml
Auto visualization and vimlAuto visualization and viml
Auto visualization and vimlBill Liu
 
Explainability and bias in AI
Explainability and bias in AIExplainability and bias in AI
Explainability and bias in AIBill Liu
 
An Introduction to Neural Architecture Search
An Introduction to Neural Architecture SearchAn Introduction to Neural Architecture Search
An Introduction to Neural Architecture SearchBill Liu
 
weekly AI tech talk #85 ml-agents Enabling Learned Behaviors with Reinforceme...
weekly AI tech talk #85 ml-agents Enabling Learned Behaviors with Reinforceme...weekly AI tech talk #85 ml-agents Enabling Learned Behaviors with Reinforceme...
weekly AI tech talk #85 ml-agents Enabling Learned Behaviors with Reinforceme...Bill Liu
 
Data stream with cruise control
Data stream with cruise controlData stream with cruise control
Data stream with cruise controlBill Liu
 
AI in linkedin
AI in linkedinAI in linkedin
AI in linkedinBill Liu
 

More from Bill Liu (20)

Walk Through a Real World ML Production Project
Walk Through a Real World ML Production ProjectWalk Through a Real World ML Production Project
Walk Through a Real World ML Production Project
 
Redefining MLOps with Model Deployment, Management and Observability in Produ...
Redefining MLOps with Model Deployment, Management and Observability in Produ...Redefining MLOps with Model Deployment, Management and Observability in Produ...
Redefining MLOps with Model Deployment, Management and Observability in Produ...
 
Productizing Machine Learning at the Edge
Productizing Machine Learning at the EdgeProductizing Machine Learning at the Edge
Productizing Machine Learning at the Edge
 
Transformers in Vision: From Zero to Hero
Transformers in Vision: From Zero to HeroTransformers in Vision: From Zero to Hero
Transformers in Vision: From Zero to Hero
 
Practical Crowdsourcing for ML at Scale
Practical Crowdsourcing for ML at ScalePractical Crowdsourcing for ML at Scale
Practical Crowdsourcing for ML at Scale
 
Building large scale transactional data lake using apache hudi
Building large scale transactional data lake using apache hudiBuilding large scale transactional data lake using apache hudi
Building large scale transactional data lake using apache hudi
 
Deep Reinforcement Learning and Its Applications
Deep Reinforcement Learning and Its ApplicationsDeep Reinforcement Learning and Its Applications
Deep Reinforcement Learning and Its Applications
 
Big Data and AI in Fighting Against COVID-19
Big Data and AI in Fighting Against COVID-19Big Data and AI in Fighting Against COVID-19
Big Data and AI in Fighting Against COVID-19
 
Build computer vision models to perform object detection and classification w...
Build computer vision models to perform object detection and classification w...Build computer vision models to perform object detection and classification w...
Build computer vision models to perform object detection and classification w...
 
Causal Inference in Data Science and Machine Learning
Causal Inference in Data Science and Machine LearningCausal Inference in Data Science and Machine Learning
Causal Inference in Data Science and Machine Learning
 
AISF19 - On Blending Machine Learning with Microeconomics
AISF19 - On Blending Machine Learning with MicroeconomicsAISF19 - On Blending Machine Learning with Microeconomics
AISF19 - On Blending Machine Learning with Microeconomics
 
AISF19 - Travel in the AI-First World
AISF19 - Travel in the AI-First WorldAISF19 - Travel in the AI-First World
AISF19 - Travel in the AI-First World
 
Toronto meetup 20190917
Toronto meetup 20190917Toronto meetup 20190917
Toronto meetup 20190917
 
Feature Engineering for NLP
Feature Engineering for NLPFeature Engineering for NLP
Feature Engineering for NLP
 
Auto visualization and viml
Auto visualization and vimlAuto visualization and viml
Auto visualization and viml
 
Explainability and bias in AI
Explainability and bias in AIExplainability and bias in AI
Explainability and bias in AI
 
An Introduction to Neural Architecture Search
An Introduction to Neural Architecture SearchAn Introduction to Neural Architecture Search
An Introduction to Neural Architecture Search
 
weekly AI tech talk #85 ml-agents Enabling Learned Behaviors with Reinforceme...
weekly AI tech talk #85 ml-agents Enabling Learned Behaviors with Reinforceme...weekly AI tech talk #85 ml-agents Enabling Learned Behaviors with Reinforceme...
weekly AI tech talk #85 ml-agents Enabling Learned Behaviors with Reinforceme...
 
Data stream with cruise control
Data stream with cruise controlData stream with cruise control
Data stream with cruise control
 
AI in linkedin
AI in linkedinAI in linkedin
AI in linkedin
 

Recently uploaded

Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsSnow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsHyundai Motor Group
 
costume and set research powerpoint presentation
costume and set research powerpoint presentationcostume and set research powerpoint presentation
costume and set research powerpoint presentationphoebematthew05
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
Key Features Of Token Development (1).pptx
Key Features Of Token Development (1).pptxKey Features Of Token Development (1).pptx
Key Features Of Token Development (1).pptxLBM Solutions
 
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxMaking_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxnull - The Open Security Community
 
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024BookNet Canada
 
Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Neo4j
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubKalema Edgar
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraDeakin University
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April Automation LPDGAPIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April Automation LPDGMarianaLemus7
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsAndrey Dotsenko
 
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
Unlocking the Potential of the Cloud for IBM Power Systems
Unlocking the Potential of the Cloud for IBM Power SystemsUnlocking the Potential of the Cloud for IBM Power Systems
Unlocking the Potential of the Cloud for IBM Power SystemsPrecisely
 

Recently uploaded (20)

Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter RoadsSnow Chain-Integrated Tire for a Safe Drive on Winter Roads
Snow Chain-Integrated Tire for a Safe Drive on Winter Roads
 
costume and set research powerpoint presentation
costume and set research powerpoint presentationcostume and set research powerpoint presentation
costume and set research powerpoint presentation
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
Key Features Of Token Development (1).pptx
Key Features Of Token Development (1).pptxKey Features Of Token Development (1).pptx
Key Features Of Token Development (1).pptx
 
The transition to renewables in India.pdf
The transition to renewables in India.pdfThe transition to renewables in India.pdf
The transition to renewables in India.pdf
 
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxMaking_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
 
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
 
Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024Build your next Gen AI Breakthrough - April 2024
Build your next Gen AI Breakthrough - April 2024
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
Artificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning eraArtificial intelligence in the post-deep learning era
Artificial intelligence in the post-deep learning era
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April Automation LPDGAPIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April Automation LPDG
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping Elbows
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
Pigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food ManufacturingPigging Solutions in Pet Food Manufacturing
Pigging Solutions in Pet Food Manufacturing
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
Unlocking the Potential of the Cloud for IBM Power Systems
Unlocking the Potential of the Cloud for IBM Power SystemsUnlocking the Potential of the Cloud for IBM Power Systems
Unlocking the Potential of the Cloud for IBM Power Systems
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 

Weekly #106: Deep Learning on Mobile