SlideShare a Scribd company logo
Open Source AI / ML Technologies and Application for
Product Development
Chetan Khatri, India
HKOSCon, 2018
@khatri_chetan
Hong Kong Open Source Conference 2018
Charles K Kao Auditorium and Conference Hall 4-7, Hong Kong Science Park,
Shatin. Hong Kong.

Chetan Khatri
Lead - Data Science, Accionlabs Inc.
Open Source Contributor: Apache
Spark, Apache HBase, Elixir Lang.
Alumni - University of Kachchh.
HKOSCon 2018,
Hong Kong Science Park,
Shatin. Hong Kong
WHO AM I ?
Lead - Data Science, Technology Evangelist @ Accion labs India Pvt. Ltd.
Committer @ Apache Spark, Apache HBase, Elixir Lang.
Co-Authored University Curriculum @ University of Kachchh.
Data Engineering @: Nazara Games, Eccella Corporation.
M.Sc. - Computer Science from University of Kachchh.
What is Artificial Intelligence ?
“Artificial intelligence is intelligence demonstrated by machines, in contrast to the natural intelligence
displayed by humans and other animals”. - Wikipedia
The Original definition of A.I:
“Every aspect of learning or any other feature of intelligence can in principle be so precisely described
that a machine can be made it simulate it. An attempt will be made to find how to make machines use
language, form abstractions and concepts, solve kinds of problems now reserved for humans, and
improve themselves”.
- John McCarthy at Dartmouth Conference. 1955
AI is new electricity!
“Software is eating the world, and A.I is eating software !”
- GPUs / TPUs are eating Linear Algebra.
- Linear Algebra is eating Deep Learning.
- Deep Learning is eating Machine Learning.
- Machine Learning is eating Artificial Intelligence (AI).
- AI is eating Software.
- Software is eating the world.
Machine learning
It is a subfield of AI concerned with algorithms that allow computer to learn from examples/data and
experience. Machine
Learning Machine
Learning
Supervised
Learning
Unsupervised
Learning
Reinforcement
Learning
Deep Neural
Network / Deep
learning
How deep learning is different ?
Data
Feature
engineering
Statistical
Machine learning
Model
Features
Unseen Sample
Data
Deep Learning kind of
Machine learning
Model
Automatically identifies
features !
Prediction
Prediction
Unseen Sample
What is an Artificial Neural Network ?
BEACH
SEA
SKY
...
Neural Networks have been around for a while ...
… But then this happened
1
WEB-SCALE
DATA
Data volumes double
every year
… But then this happened
2
WEB-SCALE
DATA
Massive Adoption of GPU
and TPU.
… But then this happened
3
ADVANCED NEURAL
NETWORK DESIGNS
Supervised Learning !
A (INPUT) B (RESPONSE)
EMAIL SPAM ? (0/1)
IMAGE
OBJECT(1,...,10
00)
AUDIO TEXT
ENGLISH FRENCH
Machine learning / AI: Use Cases
Regression &
Classification
Real-time Data
Analysis
Character
Recognition (OCR)
ML Workload
Automation
Recommendation
& Personalization
Natural Language
Processing
Computer Vision
Data
Visualization
Information
Extraction
Deep Neural
Network
Conversational
Dialog Agent
(Bots)
Speech
Recognition
Forecasting
Predictions
Reinforcement
Learning
Scaling Prediction
services
Federated
Learning
TOOLS &
TECHNOLOGIES
Languages
Data Quality
Predictive
Modelling
Deep
Learning / AI
TOOLS &
TECHNOLOGIES
Data
Visualization
Containerized Scheduling
TOOLS &
TECHNOLOGIES
Scheduling
GPU Enabled
TOOLS &
TECHNOLOGIES
Artificial Intelligence and Machine learning
Automating the organization
Improving Decision making &
Reducing Inefficiencies
Machine learning process
Collect and
prepare
training data
Choose and
optimize your
ML algorithm
Setup and manage
environments for
training
Train and tune model
(trial and error)
Deploy model
in production
Scale and manage the
production environment
High level Architecture
BUILD TRAIN
Machine learning as
Service
ALGORITHMS
FRAMEWORKS
K-Means Clustering
Principal Component Analysis
Neural Topic Modelling
Factorization Machines
Linear Learner - Regression
Deep Reinforcement Learner
Convolutional Neural Network
XGBoost
Latent Dirichlet Allocation
Seq2Seq , LSTM
Recurrent Neural Network
Linear Learner - Classification
TensorFlow
PyTorch
Torch
Caffe2
CNTK
Caffe
Apache Spark MLlib
Apache Flink
Setup and manage
environments for
training
Train and tune
model
(trial and error)
Deploy model
in production
Scale & manage
the production
environment
Applications of AI : Computer Vision
Self-Driving
Cars
Convolution Neural
Network
Recurrent Neural
network
Vision i.e Camera Object recognition and identification
Real time, Per pixel Object Segmentation
Centimeter-accurate positioning
Applications of AI : Computer Vision
Visual Search &
Recommendation
Convolution Neural
Network
Recurrent Neural
network
Camera
Applications of AI : Computer Vision
Applications of AI : Computer Vision
Ad / User Click ? (0/1) Whether user will click to adv. or not ?
UI Wireframe UI Screen
Possible ???
Screenshot Source Code
Applications of AI : Computer Vision
Ad / User Click ? (0/1) Whether user will click to adv. or not ?
UI Wireframe UI Screen
Possible ???
Screenshot Source Code
DEMO
Applications of AI : Computer Vision - DEMO
UI Wireframe UI Screen
Applications of AI : Computer Vision - DEMO
Screenshot Source Code
Natural Language Processing
Entities
Key Phrases
Language
Sentiment
Topics
Application of AI: Natural Language Processing
Business Applications
Entity Recognition
Sentiment Analysis
Content Classification
Language Translation, Speech Recognition
Conversational Dialog Agent / Chatbots
Syntax Analysis (Key Phrases, Language
Understanding)
Techniques
Recurrent Neural Network
Latent Dirichlet Allocation (LDA)
Neural Topic Modeling
Neural Recursive Network / Attention Network
Transfer Learning
Seq-to-Seq + LSTM
Challenges
- Interoperability of Deep Learning frameworks.
- Scale Inference at Production.
- Distribution and Parallelism of ML / AI Models.
- Build reusable components that work well together (across frameworks) - UNIX Philosophy
- Train at GPU / CPU - Inference @ Mobile, Raspberry PI, Drone, Streaming Application
Facial Emotion Recognition: DEMO
1.
Facial
Emotion
Recognition
Convolution Neural
Network
Recurrent Neural
network
Vision i.e Camera
Real time object recognition : DEMO
Real time
Object
recognition
Convolution Neural
Network
Recurrent Neural
network
Vision i.e Camera
Everyone has own choice of Deep Learning
Frameworks
Research to Production
Everyone has own choice of Deep Learning
Frameworks
Reimplementation takes
Weeks or months
Deep Learning Framework Zoo
...
Framework
backends
Vendor and numeric libraries
...
O (n2
) pairs
Apple CoreML Nvidia TensorRT
Intel/Nervana
ngraph
Qualcomm SNPE
Open Neural Network Exchange (ONNX)
...
Framework
backends
Vendor and numeric libraries
...
Apple CoreML Nvidia TensorRT
Intel/Nervana
ngraph
Qualcomm SNPE
Shared model and operator representation
From O(n2
) to O(n) pairs
Train at GPU, Inference at Mobile App !
...
Apple CoreML TensorFlow Light
Thanks !
@khatri_chetan
chetan.khatri@live.com

More Related Content

What's hot

Artificial Intelligence for Business - Version 2
Artificial Intelligence for Business - Version 2Artificial Intelligence for Business - Version 2
Artificial Intelligence for Business - Version 2
Nicola Mattina
 
OCR
OCROCR
OCR
jacekb
 
Python AI tutorial
Python AI tutorialPython AI tutorial
Python AI tutorial
grinu
 
Artificial Intelligence And Its Applications
Artificial Intelligence And Its ApplicationsArtificial Intelligence And Its Applications
Artificial Intelligence And Its Applications
Knoldus Inc.
 
Artificial Intelligence (AI) Interview Questions and Answers | Edureka
Artificial Intelligence (AI) Interview Questions and Answers | EdurekaArtificial Intelligence (AI) Interview Questions and Answers | Edureka
Artificial Intelligence (AI) Interview Questions and Answers | Edureka
Edureka!
 
AI & ML
AI & MLAI & ML
AI & ML
Karan Shaw
 
Ai=ml academic-institutions-Webinar
Ai=ml academic-institutions-WebinarAi=ml academic-institutions-Webinar
Ai=ml academic-institutions-Webinar
Avishkar Soft Labs Pvt Ltd
 
Artificial intelligence
Artificial intelligenceArtificial intelligence
Artificial intelligence
Learnbay Datascience
 
Artificial intelligence original
Artificial intelligence originalArtificial intelligence original
Artificial intelligence original
Saila Sri
 
How to use Artificial Intelligence with Python? Edureka
How to use Artificial Intelligence with Python? EdurekaHow to use Artificial Intelligence with Python? Edureka
How to use Artificial Intelligence with Python? Edureka
Edureka!
 
Shift AI 2020: Using AI for automatic synthesis | Boris Cergol (Comtrade Digi...
Shift AI 2020: Using AI for automatic synthesis | Boris Cergol (Comtrade Digi...Shift AI 2020: Using AI for automatic synthesis | Boris Cergol (Comtrade Digi...
Shift AI 2020: Using AI for automatic synthesis | Boris Cergol (Comtrade Digi...
Shift Conference
 
What Is Machine Learning? | What Is Machine Learning And How Does It Work? | ...
What Is Machine Learning? | What Is Machine Learning And How Does It Work? | ...What Is Machine Learning? | What Is Machine Learning And How Does It Work? | ...
What Is Machine Learning? | What Is Machine Learning And How Does It Work? | ...
Simplilearn
 
Demystifying Ml, DL and AI
Demystifying Ml, DL and AIDemystifying Ml, DL and AI
Demystifying Ml, DL and AI
Greg Werner
 
Machine learning in startup
Machine learning in startupMachine learning in startup
Machine learning in startup
Masas Dani
 
From Narrow AI to Artificial General Intelligence (AGI)
From Narrow AI to Artificial General Intelligence (AGI)From Narrow AI to Artificial General Intelligence (AGI)
From Narrow AI to Artificial General Intelligence (AGI)
Helgi Páll Helgason, PhD
 
Intel® AI: AI Lab at Intel
Intel® AI: AI Lab at Intel Intel® AI: AI Lab at Intel
Intel® AI: AI Lab at Intel
Intel® Software
 
artificial Intelligence
artificial Intelligence artificial Intelligence
artificial Intelligence
Ramya SK
 
Bringing Machine Learning to Mobile Apps with TensorFlow
Bringing Machine Learning to Mobile Apps with TensorFlowBringing Machine Learning to Mobile Apps with TensorFlow
Bringing Machine Learning to Mobile Apps with TensorFlow
Marianne Harness
 
AI ch1
AI ch1AI ch1
AI ch1
Leia Jackson
 
Bringing Machine Learning to Mobile Apps with TensorFlow
Bringing Machine Learning to Mobile Apps with TensorFlowBringing Machine Learning to Mobile Apps with TensorFlow
Bringing Machine Learning to Mobile Apps with TensorFlow
Alaina Carter
 

What's hot (20)

Artificial Intelligence for Business - Version 2
Artificial Intelligence for Business - Version 2Artificial Intelligence for Business - Version 2
Artificial Intelligence for Business - Version 2
 
OCR
OCROCR
OCR
 
Python AI tutorial
Python AI tutorialPython AI tutorial
Python AI tutorial
 
Artificial Intelligence And Its Applications
Artificial Intelligence And Its ApplicationsArtificial Intelligence And Its Applications
Artificial Intelligence And Its Applications
 
Artificial Intelligence (AI) Interview Questions and Answers | Edureka
Artificial Intelligence (AI) Interview Questions and Answers | EdurekaArtificial Intelligence (AI) Interview Questions and Answers | Edureka
Artificial Intelligence (AI) Interview Questions and Answers | Edureka
 
AI & ML
AI & MLAI & ML
AI & ML
 
Ai=ml academic-institutions-Webinar
Ai=ml academic-institutions-WebinarAi=ml academic-institutions-Webinar
Ai=ml academic-institutions-Webinar
 
Artificial intelligence
Artificial intelligenceArtificial intelligence
Artificial intelligence
 
Artificial intelligence original
Artificial intelligence originalArtificial intelligence original
Artificial intelligence original
 
How to use Artificial Intelligence with Python? Edureka
How to use Artificial Intelligence with Python? EdurekaHow to use Artificial Intelligence with Python? Edureka
How to use Artificial Intelligence with Python? Edureka
 
Shift AI 2020: Using AI for automatic synthesis | Boris Cergol (Comtrade Digi...
Shift AI 2020: Using AI for automatic synthesis | Boris Cergol (Comtrade Digi...Shift AI 2020: Using AI for automatic synthesis | Boris Cergol (Comtrade Digi...
Shift AI 2020: Using AI for automatic synthesis | Boris Cergol (Comtrade Digi...
 
What Is Machine Learning? | What Is Machine Learning And How Does It Work? | ...
What Is Machine Learning? | What Is Machine Learning And How Does It Work? | ...What Is Machine Learning? | What Is Machine Learning And How Does It Work? | ...
What Is Machine Learning? | What Is Machine Learning And How Does It Work? | ...
 
Demystifying Ml, DL and AI
Demystifying Ml, DL and AIDemystifying Ml, DL and AI
Demystifying Ml, DL and AI
 
Machine learning in startup
Machine learning in startupMachine learning in startup
Machine learning in startup
 
From Narrow AI to Artificial General Intelligence (AGI)
From Narrow AI to Artificial General Intelligence (AGI)From Narrow AI to Artificial General Intelligence (AGI)
From Narrow AI to Artificial General Intelligence (AGI)
 
Intel® AI: AI Lab at Intel
Intel® AI: AI Lab at Intel Intel® AI: AI Lab at Intel
Intel® AI: AI Lab at Intel
 
artificial Intelligence
artificial Intelligence artificial Intelligence
artificial Intelligence
 
Bringing Machine Learning to Mobile Apps with TensorFlow
Bringing Machine Learning to Mobile Apps with TensorFlowBringing Machine Learning to Mobile Apps with TensorFlow
Bringing Machine Learning to Mobile Apps with TensorFlow
 
AI ch1
AI ch1AI ch1
AI ch1
 
Bringing Machine Learning to Mobile Apps with TensorFlow
Bringing Machine Learning to Mobile Apps with TensorFlowBringing Machine Learning to Mobile Apps with TensorFlow
Bringing Machine Learning to Mobile Apps with TensorFlow
 

Similar to HKOSCon18 - Chetan Khatri - Open Source AI / ML Technologies and Application for Product Development

unleshing the the Power Azure Open AI - MCT Summit middle east 2024 Riyhad.pptx
unleshing the the Power Azure Open AI - MCT Summit middle east 2024 Riyhad.pptxunleshing the the Power Azure Open AI - MCT Summit middle east 2024 Riyhad.pptx
unleshing the the Power Azure Open AI - MCT Summit middle east 2024 Riyhad.pptx
Usama Wahab Khan Cloud, Data and AI
 
Artificial Intelligence
Artificial IntelligenceArtificial Intelligence
Artificial Intelligence
Javaria Chiragh
 
Artificial Intelligence and Machine Learning
Artificial Intelligence and Machine LearningArtificial Intelligence and Machine Learning
Artificial Intelligence and Machine Learning
Mykola Dobrochynskyy
 
Filip Maertens - AI, Machine Learning and Chatbots: Think AI-first
Filip Maertens - AI, Machine Learning and Chatbots: Think AI-first Filip Maertens - AI, Machine Learning and Chatbots: Think AI-first
Filip Maertens - AI, Machine Learning and Chatbots: Think AI-first
Patrick Van Renterghem
 
a-i-presentation-121229232307-phpapp02 (2) (2).pptx
a-i-presentation-121229232307-phpapp02 (2) (2).pptxa-i-presentation-121229232307-phpapp02 (2) (2).pptx
a-i-presentation-121229232307-phpapp02 (2) (2).pptx
AYESHASIDDIQA702386
 
a-i-presentation-121229232307-phpapp02 (2) (2).pptx
a-i-presentation-121229232307-phpapp02 (2) (2).pptxa-i-presentation-121229232307-phpapp02 (2) (2).pptx
a-i-presentation-121229232307-phpapp02 (2) (2).pptx
AYESHASIDDIQA702386
 
Machine Learning API'S By Mushahid Ali
Machine Learning API'S By Mushahid AliMachine Learning API'S By Mushahid Ali
Machine Learning API'S By Mushahid Ali
Mushahid Ali
 
Technology and AI sharing - From 2016 to Y2017 and Beyond
Technology and AI sharing - From 2016 to Y2017 and BeyondTechnology and AI sharing - From 2016 to Y2017 and Beyond
Technology and AI sharing - From 2016 to Y2017 and Beyond
James Huang
 
Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...
Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...
Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...
e-dialog GmbH
 
Facial expression recognition projc 2 (3) (1)
Facial expression recognition projc 2 (3) (1)Facial expression recognition projc 2 (3) (1)
Facial expression recognition projc 2 (3) (1)
AbhiAchalla
 
A quick peek into the word of AI
A quick peek into the word of AIA quick peek into the word of AI
A quick peek into the word of AI
Subhendu Dey
 
Art of artificial intelligence and automation
Art of artificial intelligence and automationArt of artificial intelligence and automation
Art of artificial intelligence and automation
Liew Wei Da Andrew
 
What Every Programmer has to know about AI ?
What Every Programmer has to know about AI ?What Every Programmer has to know about AI ?
What Every Programmer has to know about AI ?
BILL METANGMO TSOBZE
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
Matthew Sinclair
 
[第45回 Machine Learning 15minutes! Broadcast] Azure AI - Build 2020 Updates
[第45回 Machine Learning 15minutes! Broadcast] Azure AI - Build 2020 Updates[第45回 Machine Learning 15minutes! Broadcast] Azure AI - Build 2020 Updates
[第45回 Machine Learning 15minutes! Broadcast] Azure AI - Build 2020 Updates
Naoki (Neo) SATO
 
AN INTRODUCTION TO EMERGING TECHNOLOGY
AN INTRODUCTION TO EMERGING TECHNOLOGYAN INTRODUCTION TO EMERGING TECHNOLOGY
AN INTRODUCTION TO EMERGING TECHNOLOGY
Vijay R. Joshi
 
How to Get Started in ML?
How to Get Started in ML?How to Get Started in ML?
How to Get Started in ML?
The Wisdom Daily
 
Lesson 1 intro to ai
Lesson 1   intro to aiLesson 1   intro to ai
Lesson 1 intro to ai
ankit_ppt
 
Aritficial intelligence
Aritficial intelligenceAritficial intelligence
Aritficial intelligence
Maqsood Awan
 
Lecture 1- Artificial Intelligence - Introduction
Lecture 1- Artificial Intelligence - IntroductionLecture 1- Artificial Intelligence - Introduction
Lecture 1- Artificial Intelligence - Introduction
Student at University Of Malakand, Pakistan
 

Similar to HKOSCon18 - Chetan Khatri - Open Source AI / ML Technologies and Application for Product Development (20)

unleshing the the Power Azure Open AI - MCT Summit middle east 2024 Riyhad.pptx
unleshing the the Power Azure Open AI - MCT Summit middle east 2024 Riyhad.pptxunleshing the the Power Azure Open AI - MCT Summit middle east 2024 Riyhad.pptx
unleshing the the Power Azure Open AI - MCT Summit middle east 2024 Riyhad.pptx
 
Artificial Intelligence
Artificial IntelligenceArtificial Intelligence
Artificial Intelligence
 
Artificial Intelligence and Machine Learning
Artificial Intelligence and Machine LearningArtificial Intelligence and Machine Learning
Artificial Intelligence and Machine Learning
 
Filip Maertens - AI, Machine Learning and Chatbots: Think AI-first
Filip Maertens - AI, Machine Learning and Chatbots: Think AI-first Filip Maertens - AI, Machine Learning and Chatbots: Think AI-first
Filip Maertens - AI, Machine Learning and Chatbots: Think AI-first
 
a-i-presentation-121229232307-phpapp02 (2) (2).pptx
a-i-presentation-121229232307-phpapp02 (2) (2).pptxa-i-presentation-121229232307-phpapp02 (2) (2).pptx
a-i-presentation-121229232307-phpapp02 (2) (2).pptx
 
a-i-presentation-121229232307-phpapp02 (2) (2).pptx
a-i-presentation-121229232307-phpapp02 (2) (2).pptxa-i-presentation-121229232307-phpapp02 (2) (2).pptx
a-i-presentation-121229232307-phpapp02 (2) (2).pptx
 
Machine Learning API'S By Mushahid Ali
Machine Learning API'S By Mushahid AliMachine Learning API'S By Mushahid Ali
Machine Learning API'S By Mushahid Ali
 
Technology and AI sharing - From 2016 to Y2017 and Beyond
Technology and AI sharing - From 2016 to Y2017 and BeyondTechnology and AI sharing - From 2016 to Y2017 and Beyond
Technology and AI sharing - From 2016 to Y2017 and Beyond
 
Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...
Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...
Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...
 
Facial expression recognition projc 2 (3) (1)
Facial expression recognition projc 2 (3) (1)Facial expression recognition projc 2 (3) (1)
Facial expression recognition projc 2 (3) (1)
 
A quick peek into the word of AI
A quick peek into the word of AIA quick peek into the word of AI
A quick peek into the word of AI
 
Art of artificial intelligence and automation
Art of artificial intelligence and automationArt of artificial intelligence and automation
Art of artificial intelligence and automation
 
What Every Programmer has to know about AI ?
What Every Programmer has to know about AI ?What Every Programmer has to know about AI ?
What Every Programmer has to know about AI ?
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
 
[第45回 Machine Learning 15minutes! Broadcast] Azure AI - Build 2020 Updates
[第45回 Machine Learning 15minutes! Broadcast] Azure AI - Build 2020 Updates[第45回 Machine Learning 15minutes! Broadcast] Azure AI - Build 2020 Updates
[第45回 Machine Learning 15minutes! Broadcast] Azure AI - Build 2020 Updates
 
AN INTRODUCTION TO EMERGING TECHNOLOGY
AN INTRODUCTION TO EMERGING TECHNOLOGYAN INTRODUCTION TO EMERGING TECHNOLOGY
AN INTRODUCTION TO EMERGING TECHNOLOGY
 
How to Get Started in ML?
How to Get Started in ML?How to Get Started in ML?
How to Get Started in ML?
 
Lesson 1 intro to ai
Lesson 1   intro to aiLesson 1   intro to ai
Lesson 1 intro to ai
 
Aritficial intelligence
Aritficial intelligenceAritficial intelligence
Aritficial intelligence
 
Lecture 1- Artificial Intelligence - Introduction
Lecture 1- Artificial Intelligence - IntroductionLecture 1- Artificial Intelligence - Introduction
Lecture 1- Artificial Intelligence - Introduction
 

More from Chetan Khatri

Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
Chetan Khatri
 
Demystify Information Security & Threats for Data-Driven Platforms With Cheta...
Demystify Information Security & Threats for Data-Driven Platforms With Cheta...Demystify Information Security & Threats for Data-Driven Platforms With Cheta...
Demystify Information Security & Threats for Data-Driven Platforms With Cheta...
Chetan Khatri
 
PyconZA19-Distributed-workloads-challenges-with-PySpark-and-Airflow
PyconZA19-Distributed-workloads-challenges-with-PySpark-and-AirflowPyconZA19-Distributed-workloads-challenges-with-PySpark-and-Airflow
PyconZA19-Distributed-workloads-challenges-with-PySpark-and-Airflow
Chetan Khatri
 
ScalaTo July 2019 - No more struggles with Apache Spark workloads in production
ScalaTo July 2019 - No more struggles with Apache Spark workloads in productionScalaTo July 2019 - No more struggles with Apache Spark workloads in production
ScalaTo July 2019 - No more struggles with Apache Spark workloads in production
Chetan Khatri
 
No more struggles with Apache Spark workloads in production
No more struggles with Apache Spark workloads in productionNo more struggles with Apache Spark workloads in production
No more struggles with Apache Spark workloads in production
Chetan Khatri
 
PyConLT19-No_more_struggles_with_Apache_Spark_(PySpark)_workloads_in_production
PyConLT19-No_more_struggles_with_Apache_Spark_(PySpark)_workloads_in_productionPyConLT19-No_more_struggles_with_Apache_Spark_(PySpark)_workloads_in_production
PyConLT19-No_more_struggles_with_Apache_Spark_(PySpark)_workloads_in_production
Chetan Khatri
 
Automate ml workflow_transmogrif_ai-_chetan_khatri_berlin-scala
Automate ml workflow_transmogrif_ai-_chetan_khatri_berlin-scalaAutomate ml workflow_transmogrif_ai-_chetan_khatri_berlin-scala
Automate ml workflow_transmogrif_ai-_chetan_khatri_berlin-scala
Chetan Khatri
 
HBaseConAsia 2018 - Scaling 30 TB's of Data lake with Apache HBase and Scala ...
HBaseConAsia 2018 - Scaling 30 TB's of Data lake with Apache HBase and Scala ...HBaseConAsia 2018 - Scaling 30 TB's of Data lake with Apache HBase and Scala ...
HBaseConAsia 2018 - Scaling 30 TB's of Data lake with Apache HBase and Scala ...
Chetan Khatri
 
TransmogrifAI - Automate Machine Learning Workflow with the power of Scala an...
TransmogrifAI - Automate Machine Learning Workflow with the power of Scala an...TransmogrifAI - Automate Machine Learning Workflow with the power of Scala an...
TransmogrifAI - Automate Machine Learning Workflow with the power of Scala an...
Chetan Khatri
 
An Introduction to Spark with Scala
An Introduction to Spark with ScalaAn Introduction to Spark with Scala
An Introduction to Spark with Scala
Chetan Khatri
 
HBase with Apache Spark POC Demo
HBase with Apache Spark POC DemoHBase with Apache Spark POC Demo
HBase with Apache Spark POC Demo
Chetan Khatri
 
HKOSCon18 - Chetan Khatri - Scaling TB's of Data with Apache Spark and Scala ...
HKOSCon18 - Chetan Khatri - Scaling TB's of Data with Apache Spark and Scala ...HKOSCon18 - Chetan Khatri - Scaling TB's of Data with Apache Spark and Scala ...
HKOSCon18 - Chetan Khatri - Scaling TB's of Data with Apache Spark and Scala ...
Chetan Khatri
 
Fossasia 2018-chetan-khatri
Fossasia 2018-chetan-khatriFossasia 2018-chetan-khatri
Fossasia 2018-chetan-khatri
Chetan Khatri
 
An Introduction Linear Algebra for Neural Networks and Deep learning
An Introduction Linear Algebra for Neural Networks and Deep learningAn Introduction Linear Algebra for Neural Networks and Deep learning
An Introduction Linear Algebra for Neural Networks and Deep learning
Chetan Khatri
 
Introduction to Computer Science
Introduction to Computer ScienceIntroduction to Computer Science
Introduction to Computer Science
Chetan Khatri
 
An introduction to Git with Atlassian Suite
An introduction to Git with Atlassian SuiteAn introduction to Git with Atlassian Suite
An introduction to Git with Atlassian Suite
Chetan Khatri
 
Think machine-learning-with-scikit-learn-chetan
Think machine-learning-with-scikit-learn-chetanThink machine-learning-with-scikit-learn-chetan
Think machine-learning-with-scikit-learn-chetan
Chetan Khatri
 
A step towards machine learning at accionlabs
A step towards machine learning at accionlabsA step towards machine learning at accionlabs
A step towards machine learning at accionlabs
Chetan Khatri
 
Voltage measurement using arduino
Voltage measurement using arduinoVoltage measurement using arduino
Voltage measurement using arduino
Chetan Khatri
 
Design & Building Smart Energy Meter
Design & Building Smart Energy MeterDesign & Building Smart Energy Meter
Design & Building Smart Energy Meter
Chetan Khatri
 

More from Chetan Khatri (20)

Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
Data Science for Beginner by Chetan Khatri and Deptt. of Computer Science, Ka...
 
Demystify Information Security & Threats for Data-Driven Platforms With Cheta...
Demystify Information Security & Threats for Data-Driven Platforms With Cheta...Demystify Information Security & Threats for Data-Driven Platforms With Cheta...
Demystify Information Security & Threats for Data-Driven Platforms With Cheta...
 
PyconZA19-Distributed-workloads-challenges-with-PySpark-and-Airflow
PyconZA19-Distributed-workloads-challenges-with-PySpark-and-AirflowPyconZA19-Distributed-workloads-challenges-with-PySpark-and-Airflow
PyconZA19-Distributed-workloads-challenges-with-PySpark-and-Airflow
 
ScalaTo July 2019 - No more struggles with Apache Spark workloads in production
ScalaTo July 2019 - No more struggles with Apache Spark workloads in productionScalaTo July 2019 - No more struggles with Apache Spark workloads in production
ScalaTo July 2019 - No more struggles with Apache Spark workloads in production
 
No more struggles with Apache Spark workloads in production
No more struggles with Apache Spark workloads in productionNo more struggles with Apache Spark workloads in production
No more struggles with Apache Spark workloads in production
 
PyConLT19-No_more_struggles_with_Apache_Spark_(PySpark)_workloads_in_production
PyConLT19-No_more_struggles_with_Apache_Spark_(PySpark)_workloads_in_productionPyConLT19-No_more_struggles_with_Apache_Spark_(PySpark)_workloads_in_production
PyConLT19-No_more_struggles_with_Apache_Spark_(PySpark)_workloads_in_production
 
Automate ml workflow_transmogrif_ai-_chetan_khatri_berlin-scala
Automate ml workflow_transmogrif_ai-_chetan_khatri_berlin-scalaAutomate ml workflow_transmogrif_ai-_chetan_khatri_berlin-scala
Automate ml workflow_transmogrif_ai-_chetan_khatri_berlin-scala
 
HBaseConAsia 2018 - Scaling 30 TB's of Data lake with Apache HBase and Scala ...
HBaseConAsia 2018 - Scaling 30 TB's of Data lake with Apache HBase and Scala ...HBaseConAsia 2018 - Scaling 30 TB's of Data lake with Apache HBase and Scala ...
HBaseConAsia 2018 - Scaling 30 TB's of Data lake with Apache HBase and Scala ...
 
TransmogrifAI - Automate Machine Learning Workflow with the power of Scala an...
TransmogrifAI - Automate Machine Learning Workflow with the power of Scala an...TransmogrifAI - Automate Machine Learning Workflow with the power of Scala an...
TransmogrifAI - Automate Machine Learning Workflow with the power of Scala an...
 
An Introduction to Spark with Scala
An Introduction to Spark with ScalaAn Introduction to Spark with Scala
An Introduction to Spark with Scala
 
HBase with Apache Spark POC Demo
HBase with Apache Spark POC DemoHBase with Apache Spark POC Demo
HBase with Apache Spark POC Demo
 
HKOSCon18 - Chetan Khatri - Scaling TB's of Data with Apache Spark and Scala ...
HKOSCon18 - Chetan Khatri - Scaling TB's of Data with Apache Spark and Scala ...HKOSCon18 - Chetan Khatri - Scaling TB's of Data with Apache Spark and Scala ...
HKOSCon18 - Chetan Khatri - Scaling TB's of Data with Apache Spark and Scala ...
 
Fossasia 2018-chetan-khatri
Fossasia 2018-chetan-khatriFossasia 2018-chetan-khatri
Fossasia 2018-chetan-khatri
 
An Introduction Linear Algebra for Neural Networks and Deep learning
An Introduction Linear Algebra for Neural Networks and Deep learningAn Introduction Linear Algebra for Neural Networks and Deep learning
An Introduction Linear Algebra for Neural Networks and Deep learning
 
Introduction to Computer Science
Introduction to Computer ScienceIntroduction to Computer Science
Introduction to Computer Science
 
An introduction to Git with Atlassian Suite
An introduction to Git with Atlassian SuiteAn introduction to Git with Atlassian Suite
An introduction to Git with Atlassian Suite
 
Think machine-learning-with-scikit-learn-chetan
Think machine-learning-with-scikit-learn-chetanThink machine-learning-with-scikit-learn-chetan
Think machine-learning-with-scikit-learn-chetan
 
A step towards machine learning at accionlabs
A step towards machine learning at accionlabsA step towards machine learning at accionlabs
A step towards machine learning at accionlabs
 
Voltage measurement using arduino
Voltage measurement using arduinoVoltage measurement using arduino
Voltage measurement using arduino
 
Design & Building Smart Energy Meter
Design & Building Smart Energy MeterDesign & Building Smart Energy Meter
Design & Building Smart Energy Meter
 

Recently uploaded

Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
ginni singh$A17
 
Biometric Question Bank 2021 - 1 Soln-1.pdf
Biometric Question Bank 2021 - 1 Soln-1.pdfBiometric Question Bank 2021 - 1 Soln-1.pdf
Biometric Question Bank 2021 - 1 Soln-1.pdf
Joel Ngushwai
 
Female Girls Call Mumbai 9920725232 Unlimited Short Providing Girls Service A...
Female Girls Call Mumbai 9920725232 Unlimited Short Providing Girls Service A...Female Girls Call Mumbai 9920725232 Unlimited Short Providing Girls Service A...
Female Girls Call Mumbai 9920725232 Unlimited Short Providing Girls Service A...
45unexpected
 
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
ginni singh$A17
 
Oracle Database Desupported Features on 23ai (Part B)
Oracle Database Desupported Features on 23ai (Part B)Oracle Database Desupported Features on 23ai (Part B)
Oracle Database Desupported Features on 23ai (Part B)
Alireza Kamrani
 
potential usefulness of multi-agent maze-solving in general
potential usefulness of multi-agent maze-solving in generalpotential usefulness of multi-agent maze-solving in general
potential usefulness of multi-agent maze-solving in general
huseindihon
 
Celonis Busniess Analyst Virtual Internship.pptx
Celonis Busniess Analyst Virtual Internship.pptxCelonis Busniess Analyst Virtual Internship.pptx
Celonis Busniess Analyst Virtual Internship.pptx
AnujaGaikwad28
 
CMO MRM_May 2024 WITH BREAKDOWN AND IMPROVEMENTDATA.pdf
CMO MRM_May 2024 WITH BREAKDOWN AND IMPROVEMENTDATA.pdfCMO MRM_May 2024 WITH BREAKDOWN AND IMPROVEMENTDATA.pdf
CMO MRM_May 2024 WITH BREAKDOWN AND IMPROVEMENTDATA.pdf
IndranilDasgupta19
 
Celebrity Girls Call Andheri 9930245274 Unlimited Short Providing Girls Servi...
Celebrity Girls Call Andheri 9930245274 Unlimited Short Providing Girls Servi...Celebrity Girls Call Andheri 9930245274 Unlimited Short Providing Girls Servi...
Celebrity Girls Call Andheri 9930245274 Unlimited Short Providing Girls Servi...
revolutionary575
 
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
vrvipin164
 
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
sharonblush
 
Potential Uses of the Floyd-Warshall Algorithm as appropriate
Potential Uses of the Floyd-Warshall Algorithm as appropriatePotential Uses of the Floyd-Warshall Algorithm as appropriate
Potential Uses of the Floyd-Warshall Algorithm as appropriate
huseindihon
 
potential development of the A* search algorithm specifically
potential development of the A* search algorithm specificallypotential development of the A* search algorithm specifically
potential development of the A* search algorithm specifically
huseindihon
 
Data Preprocessing Cheatsheet for learners
Data Preprocessing Cheatsheet for learnersData Preprocessing Cheatsheet for learners
Data Preprocessing Cheatsheet for learners
mohamed Ibrahim
 
🚂🚘 Premium Girls Call Bangalore 🛵🚡000XX00000 💃 Choose Best And Top Girl Serv...
🚂🚘 Premium Girls Call Bangalore  🛵🚡000XX00000 💃 Choose Best And Top Girl Serv...🚂🚘 Premium Girls Call Bangalore  🛵🚡000XX00000 💃 Choose Best And Top Girl Serv...
🚂🚘 Premium Girls Call Bangalore 🛵🚡000XX00000 💃 Choose Best And Top Girl Serv...
bhupeshkumar0889
 
Mumbai Girls Call Mumbai 🛵🚡9910780858 💃 Choose Best And Top Girl Service And ...
Mumbai Girls Call Mumbai 🛵🚡9910780858 💃 Choose Best And Top Girl Service And ...Mumbai Girls Call Mumbai 🛵🚡9910780858 💃 Choose Best And Top Girl Service And ...
Mumbai Girls Call Mumbai 🛵🚡9910780858 💃 Choose Best And Top Girl Service And ...
norina2645
 
transgenders community data in india by govt
transgenders community data in india by govttransgenders community data in india by govt
transgenders community data in india by govt
palanisamyiiiier
 
ch8_multiplexing cs553 st07 slide share ss
ch8_multiplexing cs553 st07 slide share ssch8_multiplexing cs553 st07 slide share ss
ch8_multiplexing cs553 st07 slide share ss
MinThetLwin1
 
the unexpected potential of Dijkstra's Algorithm
the unexpected potential of Dijkstra's Algorithmthe unexpected potential of Dijkstra's Algorithm
the unexpected potential of Dijkstra's Algorithm
huseindihon
 
Towards an Analysis-Ready, Cloud-Optimised service for FAIR fusion data
Towards an Analysis-Ready, Cloud-Optimised service for FAIR fusion dataTowards an Analysis-Ready, Cloud-Optimised service for FAIR fusion data
Towards an Analysis-Ready, Cloud-Optimised service for FAIR fusion data
Samuel Jackson
 

Recently uploaded (20)

Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
 
Biometric Question Bank 2021 - 1 Soln-1.pdf
Biometric Question Bank 2021 - 1 Soln-1.pdfBiometric Question Bank 2021 - 1 Soln-1.pdf
Biometric Question Bank 2021 - 1 Soln-1.pdf
 
Female Girls Call Mumbai 9920725232 Unlimited Short Providing Girls Service A...
Female Girls Call Mumbai 9920725232 Unlimited Short Providing Girls Service A...Female Girls Call Mumbai 9920725232 Unlimited Short Providing Girls Service A...
Female Girls Call Mumbai 9920725232 Unlimited Short Providing Girls Service A...
 
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
Celebrity Girls Call Noida 9873940964 Unlimited Short Providing Girls Service...
 
Oracle Database Desupported Features on 23ai (Part B)
Oracle Database Desupported Features on 23ai (Part B)Oracle Database Desupported Features on 23ai (Part B)
Oracle Database Desupported Features on 23ai (Part B)
 
potential usefulness of multi-agent maze-solving in general
potential usefulness of multi-agent maze-solving in generalpotential usefulness of multi-agent maze-solving in general
potential usefulness of multi-agent maze-solving in general
 
Celonis Busniess Analyst Virtual Internship.pptx
Celonis Busniess Analyst Virtual Internship.pptxCelonis Busniess Analyst Virtual Internship.pptx
Celonis Busniess Analyst Virtual Internship.pptx
 
CMO MRM_May 2024 WITH BREAKDOWN AND IMPROVEMENTDATA.pdf
CMO MRM_May 2024 WITH BREAKDOWN AND IMPROVEMENTDATA.pdfCMO MRM_May 2024 WITH BREAKDOWN AND IMPROVEMENTDATA.pdf
CMO MRM_May 2024 WITH BREAKDOWN AND IMPROVEMENTDATA.pdf
 
Celebrity Girls Call Andheri 9930245274 Unlimited Short Providing Girls Servi...
Celebrity Girls Call Andheri 9930245274 Unlimited Short Providing Girls Servi...Celebrity Girls Call Andheri 9930245274 Unlimited Short Providing Girls Servi...
Celebrity Girls Call Andheri 9930245274 Unlimited Short Providing Girls Servi...
 
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
Coimbatore Girls call Service 000XX00000 Provide Best And Top Girl Service An...
 
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
Best Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...
 
Potential Uses of the Floyd-Warshall Algorithm as appropriate
Potential Uses of the Floyd-Warshall Algorithm as appropriatePotential Uses of the Floyd-Warshall Algorithm as appropriate
Potential Uses of the Floyd-Warshall Algorithm as appropriate
 
potential development of the A* search algorithm specifically
potential development of the A* search algorithm specificallypotential development of the A* search algorithm specifically
potential development of the A* search algorithm specifically
 
Data Preprocessing Cheatsheet for learners
Data Preprocessing Cheatsheet for learnersData Preprocessing Cheatsheet for learners
Data Preprocessing Cheatsheet for learners
 
🚂🚘 Premium Girls Call Bangalore 🛵🚡000XX00000 💃 Choose Best And Top Girl Serv...
🚂🚘 Premium Girls Call Bangalore  🛵🚡000XX00000 💃 Choose Best And Top Girl Serv...🚂🚘 Premium Girls Call Bangalore  🛵🚡000XX00000 💃 Choose Best And Top Girl Serv...
🚂🚘 Premium Girls Call Bangalore 🛵🚡000XX00000 💃 Choose Best And Top Girl Serv...
 
Mumbai Girls Call Mumbai 🛵🚡9910780858 💃 Choose Best And Top Girl Service And ...
Mumbai Girls Call Mumbai 🛵🚡9910780858 💃 Choose Best And Top Girl Service And ...Mumbai Girls Call Mumbai 🛵🚡9910780858 💃 Choose Best And Top Girl Service And ...
Mumbai Girls Call Mumbai 🛵🚡9910780858 💃 Choose Best And Top Girl Service And ...
 
transgenders community data in india by govt
transgenders community data in india by govttransgenders community data in india by govt
transgenders community data in india by govt
 
ch8_multiplexing cs553 st07 slide share ss
ch8_multiplexing cs553 st07 slide share ssch8_multiplexing cs553 st07 slide share ss
ch8_multiplexing cs553 st07 slide share ss
 
the unexpected potential of Dijkstra's Algorithm
the unexpected potential of Dijkstra's Algorithmthe unexpected potential of Dijkstra's Algorithm
the unexpected potential of Dijkstra's Algorithm
 
Towards an Analysis-Ready, Cloud-Optimised service for FAIR fusion data
Towards an Analysis-Ready, Cloud-Optimised service for FAIR fusion dataTowards an Analysis-Ready, Cloud-Optimised service for FAIR fusion data
Towards an Analysis-Ready, Cloud-Optimised service for FAIR fusion data
 

HKOSCon18 - Chetan Khatri - Open Source AI / ML Technologies and Application for Product Development

  • 1. Open Source AI / ML Technologies and Application for Product Development Chetan Khatri, India HKOSCon, 2018 @khatri_chetan Hong Kong Open Source Conference 2018 Charles K Kao Auditorium and Conference Hall 4-7, Hong Kong Science Park, Shatin. Hong Kong.
  • 2.  Chetan Khatri Lead - Data Science, Accionlabs Inc. Open Source Contributor: Apache Spark, Apache HBase, Elixir Lang. Alumni - University of Kachchh. HKOSCon 2018, Hong Kong Science Park, Shatin. Hong Kong
  • 3. WHO AM I ? Lead - Data Science, Technology Evangelist @ Accion labs India Pvt. Ltd. Committer @ Apache Spark, Apache HBase, Elixir Lang. Co-Authored University Curriculum @ University of Kachchh. Data Engineering @: Nazara Games, Eccella Corporation. M.Sc. - Computer Science from University of Kachchh.
  • 4. What is Artificial Intelligence ? “Artificial intelligence is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals”. - Wikipedia The Original definition of A.I: “Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made it simulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves”. - John McCarthy at Dartmouth Conference. 1955 AI is new electricity!
  • 5. “Software is eating the world, and A.I is eating software !” - GPUs / TPUs are eating Linear Algebra. - Linear Algebra is eating Deep Learning. - Deep Learning is eating Machine Learning. - Machine Learning is eating Artificial Intelligence (AI). - AI is eating Software. - Software is eating the world.
  • 6. Machine learning It is a subfield of AI concerned with algorithms that allow computer to learn from examples/data and experience. Machine Learning Machine Learning Supervised Learning Unsupervised Learning Reinforcement Learning Deep Neural Network / Deep learning
  • 7. How deep learning is different ? Data Feature engineering Statistical Machine learning Model Features Unseen Sample Data Deep Learning kind of Machine learning Model Automatically identifies features ! Prediction Prediction Unseen Sample
  • 8. What is an Artificial Neural Network ? BEACH SEA SKY ...
  • 9. Neural Networks have been around for a while ...
  • 10. … But then this happened 1 WEB-SCALE DATA Data volumes double every year
  • 11. … But then this happened 2 WEB-SCALE DATA Massive Adoption of GPU and TPU.
  • 12. … But then this happened 3 ADVANCED NEURAL NETWORK DESIGNS
  • 13. Supervised Learning ! A (INPUT) B (RESPONSE) EMAIL SPAM ? (0/1) IMAGE OBJECT(1,...,10 00) AUDIO TEXT ENGLISH FRENCH
  • 14. Machine learning / AI: Use Cases Regression & Classification Real-time Data Analysis Character Recognition (OCR) ML Workload Automation Recommendation & Personalization Natural Language Processing Computer Vision Data Visualization Information Extraction Deep Neural Network Conversational Dialog Agent (Bots) Speech Recognition Forecasting Predictions Reinforcement Learning Scaling Prediction services Federated Learning
  • 19. Artificial Intelligence and Machine learning Automating the organization Improving Decision making & Reducing Inefficiencies
  • 20. Machine learning process Collect and prepare training data Choose and optimize your ML algorithm Setup and manage environments for training Train and tune model (trial and error) Deploy model in production Scale and manage the production environment
  • 21. High level Architecture BUILD TRAIN Machine learning as Service ALGORITHMS FRAMEWORKS K-Means Clustering Principal Component Analysis Neural Topic Modelling Factorization Machines Linear Learner - Regression Deep Reinforcement Learner Convolutional Neural Network XGBoost Latent Dirichlet Allocation Seq2Seq , LSTM Recurrent Neural Network Linear Learner - Classification TensorFlow PyTorch Torch Caffe2 CNTK Caffe Apache Spark MLlib Apache Flink Setup and manage environments for training Train and tune model (trial and error) Deploy model in production Scale & manage the production environment
  • 22. Applications of AI : Computer Vision Self-Driving Cars Convolution Neural Network Recurrent Neural network Vision i.e Camera Object recognition and identification Real time, Per pixel Object Segmentation Centimeter-accurate positioning
  • 23. Applications of AI : Computer Vision Visual Search & Recommendation Convolution Neural Network Recurrent Neural network Camera
  • 24. Applications of AI : Computer Vision
  • 25. Applications of AI : Computer Vision Ad / User Click ? (0/1) Whether user will click to adv. or not ? UI Wireframe UI Screen Possible ??? Screenshot Source Code
  • 26. Applications of AI : Computer Vision Ad / User Click ? (0/1) Whether user will click to adv. or not ? UI Wireframe UI Screen Possible ??? Screenshot Source Code DEMO
  • 27. Applications of AI : Computer Vision - DEMO UI Wireframe UI Screen
  • 28. Applications of AI : Computer Vision - DEMO Screenshot Source Code
  • 29. Natural Language Processing Entities Key Phrases Language Sentiment Topics
  • 30. Application of AI: Natural Language Processing Business Applications Entity Recognition Sentiment Analysis Content Classification Language Translation, Speech Recognition Conversational Dialog Agent / Chatbots Syntax Analysis (Key Phrases, Language Understanding) Techniques Recurrent Neural Network Latent Dirichlet Allocation (LDA) Neural Topic Modeling Neural Recursive Network / Attention Network Transfer Learning Seq-to-Seq + LSTM
  • 31. Challenges - Interoperability of Deep Learning frameworks. - Scale Inference at Production. - Distribution and Parallelism of ML / AI Models. - Build reusable components that work well together (across frameworks) - UNIX Philosophy - Train at GPU / CPU - Inference @ Mobile, Raspberry PI, Drone, Streaming Application
  • 32. Facial Emotion Recognition: DEMO 1. Facial Emotion Recognition Convolution Neural Network Recurrent Neural network Vision i.e Camera
  • 33. Real time object recognition : DEMO Real time Object recognition Convolution Neural Network Recurrent Neural network Vision i.e Camera
  • 34. Everyone has own choice of Deep Learning Frameworks
  • 35. Research to Production Everyone has own choice of Deep Learning Frameworks Reimplementation takes Weeks or months
  • 36. Deep Learning Framework Zoo ... Framework backends Vendor and numeric libraries ... O (n2 ) pairs Apple CoreML Nvidia TensorRT Intel/Nervana ngraph Qualcomm SNPE
  • 37. Open Neural Network Exchange (ONNX) ... Framework backends Vendor and numeric libraries ... Apple CoreML Nvidia TensorRT Intel/Nervana ngraph Qualcomm SNPE Shared model and operator representation From O(n2 ) to O(n) pairs
  • 38. Train at GPU, Inference at Mobile App ! ... Apple CoreML TensorFlow Light