amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

awesome-public-datasets

A topic-centric list of high-quality open datasets in public domains. New PR ☛☛☛

aws

azure_ml

ctci-6th-edition-python

Cracking the Coding Interview 6th Ed. Python Solutions

ctci-solutions

Python solutions to Cracking the Coding Interview (6th edition)

data-science-learning-tools-

data-structure-and-algorithm-

datasci_course_materials

Public repository for course materials for the Data Science at Scale Specialization at Coursera

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

drifter_ml

A machine learning testing framework for sklearn and pandas. The goal is to help folks assess whether things have changed over time.

ds-take-home

My solution to the book A Collection of Data Science Take-Home Challenges

eta-vs-omega

explainable_ai

Survey of few interpretable machine learning techniques. Included: SHAP, Tabular Data, LightGBM, Partial Dependence, LIME

fire_detection_model

A CNN based fire detection model using TensorFlow (Keras) and transfer learning. Includes a Python script to scrap image data from the web.

fraud-detection-using-machine-learning

Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker

industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

keras

machine-learning-books-with-python

Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python

machine-learning-notes

machine-learning-systems-design

A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"

machine_learning-

Python code on various machine learning models.

metaflow

Build and manage real-life data science projects with ease.

ml-examples-

Classification, Regression, Neural Network, Natural Language Processing

ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

physics-

This contains some of the mathematica notebooks that I developed in my earlier stages of PhD research. It includes calculation of fluctuation equations on various blackbrane solutions and calculating their corresponding quasinormal modes.

prototype_models

psycho

pyspark_tutorial

Implementation of Spark code in Jupyter notebook. Topics include: RDDs and DataFrame, exploratory data analysis (EDA), handling multiple DataFrames, visualization, Machine Learning