vybhavk Goto Github PK

learning-apache-spark

Notes on Apache Spark (pyspark)

learning-pyspark

Code repository for Learning PySpark by Packt

learning-tensorflow

learningscalamaterials

My own work on the materials of the book "Learning Scala", by Jason Swartz. MIT License

lectures

Oxford Deep NLP 2017 course

lectures-labs

Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay

lenet-in-tensorflow

Implementation of the LeNet-5 deep neural network model in Tensorflow

lime

Lime: Explaining the predictions of any machine learning classifier

lstm---stock-prediction

A long term short term memory recurrent neural network to predict stock data time series

lung_cancer_2017

machine-learning

Workshop on Machine Learning in Python

machine-learning-1

:earth_americas: machine learning algorithms tutorials (mainly in Python3)

machine-learning-links-and-lessons-learned

List of all the lessons learned, best practices, and links from my time studying machine learning

machine-learning-projects

This is my collection of Machine Learning mini-projects as I'm learning ML.

machine-learning-tutorials

machine learning and deep learning tutorials, articles and other resources

markov-chain-for-text

An implementation of second-order Markov chains for text generation

masterthesis

mememoji

A facial expression classification system that recognizes 6 basic emotions: happy, sad, surprise, fear, anger and neutral.

metrics

Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave

ml-flashcards-python

Python script to pull machine learning flashcards from Chris Albon's twitter feed

ml-from-scratch

Bare bones Python implementations of some of the foundational Machine Learning models and algorithms.

mljar-api-python

A simple python wrapper over MLJAR API.

mljar-examples

Examples how MLJAR can be used

mlpb

Machine Learning Problem Bible

models_python

My personal toolkit of classification and regression algorithms

models_r

Cross-Validation functions for various models in R

modelutils

A set of model utility Classes and functions in python

mooc-setup

Information for setting up for the BerkeleyX Spark Intro MOOC, and lab assignments for the course

moviesuccessprediction

A machine learning project to predict if a movie is going to be a blockbuster or flop. In this project we aim to collect data from various sources like Twitter and Youtube comments, and perform classification of postivity of these tweets and comments. Our model uses these values to predict success of a movie in the scale of 1 to 5, where 5 being blockbuster and 1 being flop. Various classification algorithms like SVM, Naive Bayes, Maximum Entropy are implemented and accuracy is compared. We uses Python as primary language of implementation.

multi-class-text-classification-cnn-rnn

Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.