Linear Algebra; Multivariate Calculus; Optimization; Probability and Statistics; Phenomena in High Dimensions; Approximation Theory; Functional Analysis, etc..
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Updated
Jan 11, 2020
Linear Algebra; Multivariate Calculus; Optimization; Probability and Statistics; Phenomena in High Dimensions; Approximation Theory; Functional Analysis, etc..
Repo contains miscellaneous programs
Replay Buffer is a blog on machine learning, computer science and mathematics.
These are the handwritten notes on, how to set up an IDE, an introduction to Conda environment, how to use Git and GitHub for version control, and mathematics for data science.
Companion webpage to the book "Mathematics For Machine Learning"
I)Testing and practicing different machine learning algorithms II) Mathematical modeling and simulation algorithms.
Mathematics for Machine Learning Computer Project
Anonymous Data Scientist
Assignments for lesson: Pattern Recognition - Machine Learning (UOA)
Research project on random forests and how can one improve their prediction accuracy for the NASA airfoil learning problem using mathematical analysis
Data Science With Python->Target: AI/ML
Official Repository for Pydata Pune Meetup - Gang Up -I
Personal Research on the mathematical foundation of CNNs as well as my first computer vision problem
My Collection of Certificates!
My personal notes for learning about programming and math (in particular statistics). So far it's mostly just my solutions to book exercises, maybe I'll write up some things later on. This repo consists of my studying after leaving university, I won't upload the notes from before that.
Notes taken during studying mathematics and machine learning
This repository contains a comprehensive collection of mathematical concepts and techniques relevant to various fields of AI, including ML, DL & other areas.It also includes the corresponding source code for all programming tasks associated with the Mathematics for Machine Learning courses, which are taught at Coursera by Imperial College London.
A walk through of the creation of a deep neural network from scratch!
Notes from Mathematics for Machine Learning and Data Science Specialization
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