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amazon-sagemaker-examples

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

av-timeseries-hackathon

Analytics Vidhya conducted a hackathon on the 2nd of May for predicting Energy consumption on time series data

data-engineering-for-data-scientists

Set of tools, frameworks and platforms to turn a Python ML model into an end-to-end solution that can be consumed via REST API

deployment-of-ml-models

End-to-end ML pipeline for deployment

feature-engineering-for-ml

Various techniques to preprocess data before feeding into a machine learning model

feature-selection-for-ml

Various techniques (Filter, Wrapper and Embedded Methods) to select features from training data after feature engineering & preprocessing but before feeding into the model

manning_reviews

Live projects and book reviews

ml-to-production-toolkit

Best practices for Model build governance, Environment/package management, ML Interpretability & Cloud Hosting cost estimation

predicting-credit-card-fraud

Contains the Jupyter notebook for predictive modelling of credit card frauds

predicting-customer-churn

Contains 5 Jupyter notebooks

predicting-financial-bankruptcy

Machine Learning series to analyze and predict which customers will be financially delinquent in the next 2 years. The original dataset is present in the Kaggle website (https://www.kaggle.com/c/GiveMeSomeCredit/data)

retailrecommender

UCI dataset on a UK online retailer

sigir-ecom-data-challenge

tensorflow-extended

ML platform implemented by Google for simplifying the development of end-to-end ML pipelines. TFX is used for Data Analysis/Transformation/Validation, Model Training/Evaluation/Validation and Serving

unsupervised-learning-techniques

Recommender System using Restricted Boltzman Machines (RBMs), Deep Belief Networks (DBNs), Generative Adversarial Networks (GANs)

zero-to-agile-ds

Collection of solved Data Science problems for various business use cases structured from simple to the complex