Deep Lake: Database for AI Docs • Get Started • API Reference • LangChain & VectorDBs Course • Blog • Whitepaper • Slack • Twitter Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Storing and searching data plus vectors while building LLM applications 2.
This newer video covers the an updated 2024 version of the state of MLOps. You can join the Machine Learning Engineer newsletter.
Build, test, and deploy ML-driven trading strategies — from data sourcing to live execution. This repository hosts the code for Machine Learning for Trading, 3rd Edition by Stefan Jansen — a ground-up rebuild, organized around one end-to-end workflow: how you define a research idea and develop it iteratively into a strategy you can actually run, and keep running, in a live market.
Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose of this project is not to produce as optimized and computationally efficient algorithms as possible but rather to present the inner workings of them in a transparent and accessible way.
To generate the documentation, you first have to build it. You don't have to commit the built documentation.
I will be updating this tutorials site on a daily basis adding all relevant topcis for 2022 - 2024 especially pertaining to GPU programming, Data Centric AI, Emerging topics like Sustainable AI with Web3AI.js (DeFI, DAO, NFT) and much more. NOTE: All these tutorials are supported and accelerated on NVIDIA GPUs More importantly the applications of ML/DL/AI into industry areas such as Transportation, Medicine/Healthcare etc.
Geospatial analysis, or just spatial analysis, is an approach to applying statistical analysis and other analytic techniques to data which has a geographical or spatial aspect. with GNSS (global navigation satellite system).
Awesome Prompt Engineering 🧙♂️ A hand-curated collection of resources for Prompt Engineering and Context Engineering — covering papers, tools, models, APIs, benchmarks, courses, and communities for working with Large Language Models. https://promptslab.github.io --- New to prompt engineering?
Deep Lake: Database for AI Docs • Get Started • API Reference • LangChain & VectorDBs Course • Blog • Whitepaper • Slack • Twitter Deep Lake is a Database for AI powered by a storage format optimized for deep-learning applications. Storing and searching data plus vectors while building LLM applications 2.
This newer video covers the an updated 2024 version of the state of MLOps. You can join the Machine Learning Engineer newsletter.
Build, test, and deploy ML-driven trading strategies — from data sourcing to live execution. This repository hosts the code for Machine Learning for Trading, 3rd Edition by Stefan Jansen — a ground-up rebuild, organized around one end-to-end workflow: how you define a research idea and develop it iteratively into a strategy you can actually run, and keep running, in a live market.
Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose of this project is not to produce as optimized and computationally efficient algorithms as possible but rather to present the inner workings of them in a transparent and accessible way.
To generate the documentation, you first have to build it. You don't have to commit the built documentation.
I will be updating this tutorials site on a daily basis adding all relevant topcis for 2022 - 2024 especially pertaining to GPU programming, Data Centric AI, Emerging topics like Sustainable AI with Web3AI.js (DeFI, DAO, NFT) and much more. NOTE: All these tutorials are supported and accelerated on NVIDIA GPUs More importantly the applications of ML/DL/AI into industry areas such as Transportation, Medicine/Healthcare etc.
Geospatial analysis, or just spatial analysis, is an approach to applying statistical analysis and other analytic techniques to data which has a geographical or spatial aspect. with GNSS (global navigation satellite system).
Awesome Prompt Engineering 🧙♂️ A hand-curated collection of resources for Prompt Engineering and Context Engineering — covering papers, tools, models, APIs, benchmarks, courses, and communities for working with Large Language Models. https://promptslab.github.io --- New to prompt engineering?