Simple tutorials using Google's TensorFlow Framework
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Bayesian optimization in PyTorch
🛠 All-in-one web-based IDE specialized for machine learning and data science.
Debugging, monitoring and visualization for Python Machine Learning and Data Science
Quantitative analysis, strategies and backtests
- quantitative-finance
- quantitative-trading
- portfolio-management
- risk-management
[Legacy] Data & AI Notebook templates catalog organized by tools, following the IMO (input, model, output) framework for easy usage and discovery..
- templates
- opensource
- naas
- notebooks-templates
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
An interactive data visualization tool which brings matplotlib graphics to the browser using D3.
Python Productivity for ZYNQ
- pynq
Implementing a Neural Network from Scratch
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
- deep-learning
- depth-prediction
- visual-odometry
- self-supervised-learning
Python library for interactive topic model visualization. Port of the R LDAvis package.
R kernel for Jupyter
- jupyter
- jupyter-notebook
- jupyter-kernels
- r
Koç University deep learning framework.
- knet
- deep-learning
- julia
- machine-learning
Detecting Text in Natural Image with Connectionist Text Proposal Network (ECCV'16)
- ocr
- text-detection
Collection of tools and code examples to demonstrate best practices in using Amazon EC2 Spot Instances.
Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax.
Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano
LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
- computer-vision
- visible-infrared
- low-light-image
- image-fusion
A simple Python data-structure visualization tool for lists of lists, lists, dictionaries; primarily for use in Jupyter notebooks / presentations
TensorFlow implementation of an arbitrary order Factorization Machine
- factorization-machines
- tensorflow
- research-project
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.
Move fast from data science prototype to pipeline. Capture, analyze, and transform messy notebooks into data pipelines with just two lines of code.
ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy