Kaggle-Quora-Insincere-Questions-Classification

? Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

深度学习入门教程, 优秀文章, Deep Learning Tutorial

《李宏毅深度学习教程》（李宏毅老师推荐?，苹果书?），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

Natural Language Processing Tutorial for Deep Learning Researchers

:gem: A curated list of awesome Competitive Programming, Algorithm and Data Structure resources

? Easy-to-use and powerful NLP and LLM library with ? Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including ?Text Classification, ? Neural Search, ? Question Answering, ?? Information Extraction, ? Document Intelligence, ? Sentiment Analysis etc.