scikit-learn: machine learning in Python
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Updated
Jul 12, 2024 - Python
Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge from structured and unstructured data. Data scientists perform data analysis and preparation, and their findings inform high-level decisions in many organizations.
scikit-learn: machine learning in Python
Deep Learning for humans
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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.
matplotlib: plotting with Python
A collection of machine learning examples and tutorials.
Open Machine Learning Course
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
Topic Modelling for Humans
💫 Industrial-strength Natural Language Processing (NLP) in Python
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
Best Practices on Recommendation Systems
Streamlit — A faster way to build and share data apps.
Statsmodels: statistical modeling and econometrics in Python
Deep learning library featuring a higher-level API for TensorFlow.
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.