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Learn how to design, develop, deploy and iterate on production-grade ML applications.
A game theoretic approach to explain the output of any machine learning model.
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
A guidance language for controlling large language models.
A collection of various deep learning architectures, models, and tips
The "Python Machine Learning (1st edition)" book code repository and info resource
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
TensorFlow Tutorials with YouTube Videos
Automatic extraction of relevant features from time series:
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
Recipes for using Python's pandas library
This project reproduces the book Dive Into Deep Learning (https://d2l.ai/), adapting the code from MXNet into PyTorch.
Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters
Efficient few-shot learning with Sentence Transformers
Feature selector is a tool for dimensionality reduction of machine learning datasets
Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SP…
Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for b…
A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning t…
Time series classification and clustering code written in Python.
Feature exploration for supervised learning
Notebooks for the "A walk with fastai2" Study Group and Lecture Series
JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.
DeltaPy - Tabular Data Augmentation (by @firmai)
Attempt at implementing system described in "Neural Turing Machines." by Graves, Alex, Greg Wayne, and Ivo Danihelka. (http://arxiv.org/abs/1410.5401)
Finding Lane Lines using Python and OpenCV
Implementations for my blog post [here](https://medium.com/@TalPerry/deep-learning-the-stock-market-df853d139e02#.flflpo3xf)
Passport Index 2025: visa requirements for 199 countries, in .csv