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JHipster is a development platform to quickly generate, develop, & deploy modern web applications & microservice architectures.
📝 Algorithms and data structures implemented in JavaScript with explanations and links to further readings
Interactive roadmaps, guides and other educational content to help developers grow in their careers.
Master the command line, in one page
Master programming by recreating your favorite technologies from scratch.
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
Set up the CTRL text-generating model on Google Compute Engine with just a few console commands.
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts
Code and data for paper "Deep Painterly Harmonization": https://arxiv.org/abs/1804.03189
A community driven list of useful Scala libraries, frameworks and software.
A curated list of Machine Learning Surveys, Tutorials and Books.
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
Interactive and Reactive Data Science using Scala and Spark.
Minimal and clean examples of machine learning algorithms implementations
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,…
Free resources for learning data science
A curated list of data science blogs
Open Source Data Science Resources.
Introduction to Statistics using Python
An opinionated list of Python frameworks, libraries, tools, and resources
machine learning and deep learning tutorials, articles and other resources
common data analysis and machine learning tasks using python
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow