Pinned Repositories
air
Data Engineering for Data Scientists
clairvoyance
Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series
kubernetes_example
5-Step Kubernetes CI/CD Process using Artifactory & Helm
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
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 ;)
pymc
PyMC version 3 (PyMC 2 is in branch 2.3)
ray_tutorial
An introductory tutorial about leveraging Ray core features for distributed patterns.
SIN
Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)
pgnepal's Repositories
pgnepal/ensemble-models-ML-DL-
Ensemble models, machine learning, deep learning, optimization
pgnepal/nlp_course
YSDA course in Natural Language Processing
pgnepal/RLNonStationary
Demo for the application of RL to non-stationary effects
pgnepal/tutorials-1
pgnepal/orthoml
Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Semenova, Goldman, Chernozhukov, Taddy (2017) https://arxiv.org/abs/1712.09988
pgnepal/temporal_fusion_transformer_pytorch
pgnepal/google-research
Google Research
pgnepal/photon-ml
A scalable machine learning library on Apache Spark
pgnepal/pytorch-examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
pgnepal/eng-practices
Google's Engineering Practices documentation
pgnepal/notes-on-causal-inference
Some notes on Causal Inference, with examples in python
pgnepal/interpretable_machine_learning_with_python
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
pgnepal/AttentionWalk
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
pgnepal/shopper-src
Code for Shopper, a probabilistic model of shopping baskets
pgnepal/causal_inference_python_code
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
pgnepal/classroom
GitHub Classroom automates repository creation and access control, making it easy for teachers to distribute starter code and collect assignments on GitHub.
pgnepal/Graph_Convolutional_LSTM
Traffic Graph Convolutional Recurrent Neural Network
pgnepal/horovod
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
pgnepal/stockpredictionai
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.
pgnepal/modernpython
Sample code for the video course: Modern Python: Big Ideas, Little Code
pgnepal/DLTFpT
Deep Learning with TensorFlow, Keras, and PyTorch
pgnepal/BeatTheBots
Beat The Bots Source Code
pgnepal/code_snippets
pgnepal/p9-jfrog-webinar
pgnepal/deep-learning-illustrated
Deep Learning Illustrated (2019)
pgnepal/AIF360
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
pgnepal/Machine-Learning-for-Finance
Machine Learning for Finance, published by Packt
pgnepal/tutorials
pgnepal/elements-of-python-style
Goes beyond PEP8 to discuss what makes Python code feel great. A Strunk & White for Python.
pgnepal/Quantitative_Financial_Risk_Management_with_R
Learning O'reilly: Introduction to Quantitative Financial Risk Management with R