Online Learning Path Record: Statistics & Math, Data Science, Product Management, Software Development, Quantitative Finance

I am studying Data Science. In this repository, I have written about my experiences in studying Machine learning. Also, I have included the solutions of some theoretical and practical Machine learning exercises.

Review material and practical exercises for the Machine Learning - Specialty (MLS-C01) exam

List of GitHub repositories to learn Data Structures, Algorithms and Machine Learning

Repository showing my machine-learning experiences with Python, SkLearn and Apache Spark. Providing templates to be used for standard ML problems as well for Big-Data ML problems.

Fitting a model is when you use the input data to create a predictive model. There are various metrics you can use to determine how well your model fits the data. I am using the R program to learn the basics of machine learning, from using python code, CSV files and the ggplot2, pandas, numpy and sklearn packages.

Course material and assignment repository for the "Machine Learning Foundations: A Case Study Approach" on Coursera.

Notebooks and Scripts on Machine Learning

Linear Regression , Cross Validation, k-mean clustering , Watershed , Gradients and Edge Detection , threshold , Correlation , Neural Network, Conventional Neural Network , Pneumonia Classification, Social Distancing, Rainfall Prediction, Boston Housing Price Prediction.

Machine learning is the study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. In this repository, I write code that will classify whether someone will have a greater than $80,000 income or not based on several features.

Hackerearth Machine Learning competition

Recursive gradient descent visualization as well as notes on machine learning and data science basics from Google Colab's ML Crash Course.

A biochemist note on machine learning

Learn Machine Learning Models A-Z™ And Hands-On Python In Data Science.

How to Setup Machine Learning Environment in Your PC or Laptop ? How to install Machine Learning Libraries ? How to Build ML Models, Algorithms and Other Stuff ??Your all Questions are answer here !!!!

Basic exercises on Machine Learning with Python , Refrence Book : Python for Probability, Statistics, and Machine Learning by José Unpingco

Contains resources and solutions for programming assignments for Andrew Ng's Machine learning course offered by coursera

My exercises on machine learning

Data storage, common machine learning algorithm

Classifying AI Synthesised Voice and Human Voice using Machine Learning by Spectral and Cepstral Analysis. Also classified different TTS(Text-to-Speech) engines for different AI synthesized Voice. Published Paper for the whole art of work. Link Given below.

Fun articles and tutorials to learn and review machine learning concepts. Also tired of making bookmarks, so why not organize them into a Github repo 😊

Course webpage for IIT Guwahati EE524 Machine Learning Lab (Jul-Nov 2020) Session

This project was created to facilitate an Intro to Basic Machine Learning class, organised by Ondo State Office of Innovation and Partnerships (ION).

This repo is to save the tools and code made while going through the "Introduction to Machine Learning in Python" from Andreas C. Müller & Sarah Guido - OREILLY. :)

Collection of notebooks containing NumPy implementations of the most common supervised machine learning techniques - from a simple Perceptron up to a Neural Network

This repo contains EDA of an e-Commerce company focusing on Fraud Detection, Late delivery along with RFM analysis for customer segmentation & modeling of different classification, regression models, and RNN.

📲🗜Experience how to implement Machine Learning for A/B Testing,Create a Split Object, and then Extract the Training and Testing sets🖥

This repo is for code references and mini-project for Introduction to Machine Learning.

This is a repository for short Machine Learning scripts, tools and templates that are useful for machine learning projects.