Repository Index

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

• sagemaker
• aws
• reinforcement-learning
• machine-learning

TranslatedMind maps and notes for computer science major courses (408): Computer Organization and Architecture (5th edition, Wang Aiying), Data Structures (Wangdao), Computer Networks (7th edition, Xie Xiren), Operating Systems (4th edition, Tang Xiaodan)

YSDA course in Natural Language Processing

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dmls-book`

• data-science
• machine-learning-production
• mlops

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

• deep-learning
• mit
• self-driving-cars
• deep-reinforcement-learning

TensorFlow Tutorials with YouTube Videos

• tensorflow
• deep-learning
• machine-learning
• reinforcement-learning

TensorFlow examples

• tensorflow
• tensorflow-examples

Toturials coming with the "data science roadmap" picture.

🔩 Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like Michael Bolton.

• python
• utilities
• cache
• data-structures

A course in reinforcement learning in the wild

• reinforcement-learning
• course-materials
• deep-learning
• deep-reinforcement-learning

Simple tutorials using Google's TensorFlow Framework

From the basics to slightly more interesting applications of Tensorflow

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

links to conference publications in graph-based deep learning

• graph-neural-networks
• graph-convolutional-networks
• graph
• deep-learning

A curated list of awesome Jupyter projects, libraries and resources

• jupyter-notebook
• jupyter
• jupyterhub
• jupyterlab

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

• tensorflow
• machine-learning
• regression
• convolutional-neural-networks

Deep Learning Tutorial notes and code. See the wiki for more info.

Lectures on scientific computing with python, as IPython notebooks.

KTH Algorithm Competition Template Library (... eller KTHs AC-tillverkande lapp)

• algorithm
• contest
• cpp
• data-structures

Yet another resource for collecting articles, videos etc. regarding functional programming

• awsome
• awesome-list
• functional-languages
• awesome-functional-programming

:earth_americas: machine learning tutorials (mainly in Python3)

• machine-learning
• data-science
• jupyter-notebook
• python3

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

• machine-learning
• deep-learning
• lstm
• human-activity-recognition

Open-source demos hosted on Dash Gallery

• plotly-dash
• dash
• plotly

Quantitative analysis, strategies and backtests

• quantitative-finance
• quantitative-trading
• portfolio-management
• risk-management