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hands-on-serverless-deep-learning-with-tensorflow-and-aws-lambda

Hands-On Serverless Deep Learning with TensorFlow and AWS Lambda, published by Packt

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hmmlearn

Hidden Markov Models in Python, with scikit-learn like API

hord

Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates

imagekernels

This is an extension of the excel spreadsheet used in the fast.ai course. This shows how the image kernels work and extend it to develop Convolution Neural Network.

intel-extensions-for-scikit-learn-essentials-for-machine-learning

Intel Learning

ipfr

Generic expansion of seed distribution to marginal targets

istio-example

juliacon-julia-intro

juliusgraph

Intro to Julius Graph

kaggle---google-local-visit-prediction

Prediction using BPR and LFM

keras-anomaly-detection

Anomaly detection implemented in Keras

keras-deep-learning-cookbook

Keras Deep Learning Cookbook, published by Packt

kg_game_neo4j

Knowledge Graph game designed for first time Neo4j Graph technology users

lda

Topic modeling with latent Dirichlet allocation using Gibbs sampling

learning-spark-sql

Learning Spark SQL, published by Packt

lectures

Oxford Deep NLP 2017 course

lgtm

LGTM is a simple pull request approval system [ARCHIVE]

lifelines

Survival analysis in Python

lightgbm

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

lm-glm-glmm-intro

An introduction to Linear, Generalized, and Mixed/Multilevel models with R

machine-learning-a-z

Implementation of Everything in the video lectures of Machine Learning A-Z course on Udemy by Kirill Eremenko and Hadelin de ponteves in jupyter notebook

machine-learning-for-developers

Code repository for Machine Learning for Developers, published by Packt

machine-learning-for-trading

Notebooks, resources and references accompanying the book Machine Learning for Algorithmic Trading

machinelearning_02

mariadb-and-mysql-common-table-expressions-and-window-functions-revealed

Source code for 'MariaDB and MySQL Common Table Expressions and Window Functions Revealed' by Daniel Bartholomew

market_basket_analysis

Market Basket Analysis with Recommendation Algorithms & Shiny App Implementation of a Product Recommendation System for an Online Retailer

mastering-machine-learning-with-spark-2.x

Mastering Machine Learning with Spark 2.x, published by Packt

mastering-predictive-analytics-with-r-second-edition

Mastering Predictive Analytics with R - Second Edition, published by Packt

mastering-predictive-analytics-with-scikit-learn-and-tensorflow

Published by Packt