Deep Learning for humans
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Updated
Feb 21, 2023 - 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.
Deep Learning for humans
scikit-learn: machine learning in Python
Apache Superset is a Data Visualization and Data Exploration Platform
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Learn how to responsibly develop, deploy and maintain production machine learning applications.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
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.
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.
Roadmap to becoming an Artificial Intelligence Expert in 2022
Streamlit — The fastest way to build data apps in Python
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.
Deep learning framework to train, deploy, and ship AI products Lightning fast.
Data Apps & Dashboards for Python. No JavaScript Required.
10 Weeks, 20 Lessons, Data Science for All!
The fastai book, published as Jupyter Notebooks
matplotlib: plotting with Python