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Examples and guides for using the OpenAI API
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
12 Lessons to Get Started Building AI Agents
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
Your new Mentor for Data Science E-Learning.
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
Foundational Models for State-of-the-Art Speech and Text Translation
Zero-Shot Speech Editing and Text-to-Speech in the Wild
Deploy serverless AI workflows at scale. Firebase for AI agents
Code for Tensorflow Machine Learning Cookbook
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Jupyter notebooks from the scikit-learn video series
A modern Anki custom scheduling based on Free Spaced Repetition Scheduler algorithm
A Code-First Introduction to NLP course
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
🪼 a python library for doing approximate and phonetic matching of strings.
Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE
Demo of running NNs across different frameworks
Open-source tool to visualise your RAG 🔮
An implementation of iPhone X's FaceID using face embeddings and siamese networks on RGBD images.
The hands-on NLTK tutorial for NLP in Python
LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments.
A library for developing deep generative models in a more concise, intuitive and extendable way
Codes for weekly challenges on Deep Learning by Siraj
General Assembly's Data Science course in Washington, DC
Generate chatbots from a corpus