How does the neural network work, types of neural networks, advantages and applications of neural networks, a use case of neural network, backpropagation and gradient descent, convolutional neural networks, recurrent neural network, vanishing and exploding gradient problem, long short term memory
Deep learning and its applications, Neural Network, Training Neural Networks, Deep Learning Libraries, TensorFlow, Data Flow Graph, Use Case Implementation using TensorFlow, TensorFlow Object Detection, Deep Learning Frameworks, Image Recognition, Types of Recurrent Neural Network, Working of LSTMs, Deep Learning Applications
Deep learning platforms, data flow graph, use case implementation with Tensor Flow, Linear Regression, recurrent neural network, use case implementation of RNN, Tensor Flow Object Detection API Tutorial
How does the neural network work, types of neural networks, advantages and applications of neural networks, a use case of neural network, backpropagation and gradient descent, convolutional neural networks, recurrent neural network, vanishing and exploding gradient problem, long short term memory
Deep learning and its applications, Neural Network, Training Neural Networks, Deep Learning Libraries, TensorFlow, Data Flow Graph, Use Case Implementation using TensorFlow, TensorFlow Object Detection, Deep Learning Frameworks, Image Recognition, Types of Recurrent Neural Network, Working of LSTMs, Deep Learning Applications
Deep learning platforms, data flow graph, use case implementation with Tensor Flow, Linear Regression, recurrent neural network, use case implementation of RNN, Tensor Flow Object Detection API Tutorial
Who needs to be in the team. How to set up your Board. How to select your advisors and mentors. How to create a company culture. How to use company culture to retain talent.
How to prepare for your first investment. Do you need investment. What to include in your pitch deck. How to manage relationships with investors. How to prepare for Series A.
Calculating cost, price and profit. Financial statements, profit, loss and cash flow. Thinking through equity and financial advice. Managing your day to day finances. Raising your first investment funds. Choosing between grant, debt and equity funding.
Avoiding common mistakes in building your team. Developing a compelling story about your idea. Avoiding running out of cash. Finding your early customers. Choosing the right legal structure for your business.
How to select your route to market. How to get your first 100 users. How to land your first client. How to do marketing on a budget. How to use analytics for growth. How to grow your sales. How to know everything about your customer.
Do you have the right stuff to be an entrepreneur. How entrepreneurs think up ideas. How entrepreneurs test and refine their ideas. How entrepreneurs talk to their customers. How entrepreneurs move from ideas to action. How entrepreneurs assess competition.
Marketing your business with social media. Building your communities. Sharing your content. Choosing a social media platform. Making social media work for you. Knowing when you're getting social media right.
Psychology of Search, Buying Funnel, Understanding Keyword Organisation, Keyword Match Types, Negative Keywords and Managing Search Terms, Keyword Research, Creating Compelling Ads, Advanced Ad Features, Ad Testing, Ad Extensions, Campaign Types Budget and Reach, Location and Language Targeting, Introduction to Audience Types, how to segment data and create lists
Developing a vision for content marketing success, developing business case for content marketing, creating a successful content marketing strategy, targeting customer intent instead of demographics, targeting key influencers, producing help hub and hero content consistently, producing engaging content more frequently, using effective B2C and B2B content marketing tactics, building successful B2C and B2B social media platforms, helping customers find the information they seek, helping key influences effect the buyers decision making process, measuring content effectiveness, measuring return on marketing investment, improving by experimenting with new initiatives, improving effectiveness by becoming more sophisticated and mature, content marketing in the foreseeable futur B2C evision
NoSQL Databases, CRUD Operations, Indexing and Aggregation, Replication and Sharding, Developing Java and NodeJS Application with MongoDB, MongoDB Cluster Operations
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Who needs to be in the team. How to set up your Board. How to select your advisors and mentors. How to create a company culture. How to use company culture to retain talent.
How to prepare for your first investment. Do you need investment. What to include in your pitch deck. How to manage relationships with investors. How to prepare for Series A.
Calculating cost, price and profit. Financial statements, profit, loss and cash flow. Thinking through equity and financial advice. Managing your day to day finances. Raising your first investment funds. Choosing between grant, debt and equity funding.
Avoiding common mistakes in building your team. Developing a compelling story about your idea. Avoiding running out of cash. Finding your early customers. Choosing the right legal structure for your business.
How to select your route to market. How to get your first 100 users. How to land your first client. How to do marketing on a budget. How to use analytics for growth. How to grow your sales. How to know everything about your customer.
Do you have the right stuff to be an entrepreneur. How entrepreneurs think up ideas. How entrepreneurs test and refine their ideas. How entrepreneurs talk to their customers. How entrepreneurs move from ideas to action. How entrepreneurs assess competition.
Marketing your business with social media. Building your communities. Sharing your content. Choosing a social media platform. Making social media work for you. Knowing when you're getting social media right.
Psychology of Search, Buying Funnel, Understanding Keyword Organisation, Keyword Match Types, Negative Keywords and Managing Search Terms, Keyword Research, Creating Compelling Ads, Advanced Ad Features, Ad Testing, Ad Extensions, Campaign Types Budget and Reach, Location and Language Targeting, Introduction to Audience Types, how to segment data and create lists
Developing a vision for content marketing success, developing business case for content marketing, creating a successful content marketing strategy, targeting customer intent instead of demographics, targeting key influencers, producing help hub and hero content consistently, producing engaging content more frequently, using effective B2C and B2B content marketing tactics, building successful B2C and B2B social media platforms, helping customers find the information they seek, helping key influences effect the buyers decision making process, measuring content effectiveness, measuring return on marketing investment, improving by experimenting with new initiatives, improving effectiveness by becoming more sophisticated and mature, content marketing in the foreseeable futur B2C evision
NoSQL Databases, CRUD Operations, Indexing and Aggregation, Replication and Sharding, Developing Java and NodeJS Application with MongoDB, MongoDB Cluster Operations
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).