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AutoQuantLLM is an efficient and flexible tool designed to help you quantize machine learning models with ease. Supporting multiple quantization methods and types, this tool allows you to optimize …
This Open LLM Framework serves as a powerful and flexible tool for serving endpoints for embeddings and chat completions using SOTA open source language models. By leveraging models Transformers, t…
Learn how to create, develop, and maintain a state-of-the-art MLOps code base
High-quality datasets, tools, and concepts for LLM fine-tuning.
Machine Learning and Computer Vision Engineer - Technical Interview Questions
ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.
Fetch and visualize the graph of your Twitter friends and followers.
Automatic text generation using LSTM networks for generating text similar to a given input
This is a simple Flask API that provides wine variety classification based on their descriptions. The API uses an XGBoost model and an NLTK tokenizer to perform the classification.
Interact with your documents using the power of GPT, 100% privately, no data leaks
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
A scratch implementation of Convolutional Neural Network in Python using only numpy and validated over CIFAR-10 & MNIST Dataset
Clone a voice in 5 seconds to generate arbitrary speech in real-time
Find script examples that you can run out of the box in your SingleStoreDB.
Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text…
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Automatically visualize your pandas dataframe via a single print! 📊 💡
BookNLP, a natural language processing pipeline for books
A collection of (mostly) technical things every software developer should know about
💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️
Papers from the computer science community to read and discuss.
It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced research…
Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch