100 Days of ML Coding

Implements common data science methods and machine learning algorithms from scratch in python. Intuition and theory behind the algorithms is also discussed.

The motive behind Creating this repo is to feel the fear of mathematics and do what ever you want to do in Machine Learning , Deep Learning and other fields of AI

A day to day plan for this challenge (50 Days of Machine Learning) . Covers both theoretical and practical aspects

School of AI 北京

Software to look for interrelationships between constants and find formulas for number sequences

Introduction to the concept of Generative Adversarial Networks (GANs) and the promising future

My summary for "Gradient Descent"

Coding Assignments for Siraj Raval's course of the same name

Code that list all the tweets and their sentiment analysis result that are related to any tag or word.

Homework assignments for Siraj Raval's exclusive MOOC: Make Money With Machine Learning

Challenges solved for the course of 'The Math of Intelligence' by Siraj Raval

Solutions to some of the weekly challenges on deep learning conducted by Siraj Raval

Jupyter Notebook Tutorials for Siraj Raval's Intro to Deep Learning Lectures

Some mini projects using python with reference from Siraj Raval Youtube channel

Machine learning getting started.

This repository contains the materials that I have been teaching as the dean at school of AI.

Gender classification challenge from: 'Learn Python for Data Science #1' by @Sirajology

Data Lit is is a 3 month course designed to help absolute beginners become proficient in Data Science. Each week offers lessons on Data Science fundamentals applied to real-world problems that Data Scientists help solve. After completing this course, start applying for jobs, doing contract work, start your own data science consulting group, or just keep on learning. Remember to believe in your ability to learn. You can learn data science, you will learn data science, and if you stick to it, eventually you will master it. This course starts on January 28,2019. We’re building many, many lectures for each week, expect this curriculum to get much more detailed before the course starts. Sign up now! Components 2 Projects (1 Midterm + 1 Final) 1 Weekly assignment Course Length 12 Weeks 10-15 hours per week Certification Students who successfully complete the course will receive their own certificate signed by Siraj Raval. Tools Used Python, SQL, Tensorflow, Hadoop, MapReduce, Spark, GitHub

Introductory approach to neural networks, as presented by Siraj Raval, emulating an XOR in python using only numpy

We are Classifying the Gender Of people By Knowing the Body metrics only. All hail Raval

Log of Siraj Raval's 100 Days of ML Code Challenge