This repository contains the code for all the programming tasks of the Mathematics for Machine Learning courses taught at Coursera by Imperial College London
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Updated
Sep 8, 2018 - Jupyter Notebook
This repository contains the code for all the programming tasks of the Mathematics for Machine Learning courses taught at Coursera by Imperial College London
Mathematical consequences of orthogonal weights initialization and regularization in deep learning. Experiments with gain-adjusted orthogonal regularizer on RNNs with SeqMNIST dataset.
Численные методы оптимизации реализованные для курса ВолгГТУ "Методы оптимизации"
Explanation of Mathematics used in Machine Learning Algorithms and some Projects
Blank notebooks and solutions for the Mathematics for Machine Learning specialization by Imperial College of London on Coursera.
This repository consists of my assignment submissions for Mathematics in machine Learning course by Imperial College on Coursera.
MATHEMATICS FOR MACHINE LEARNING Coursera Specialization by IMPERIAL COLLEGE LONDON
Go simple-to-use plotting library that includes visualization of vectors and matrices, the Gaussian distribution, time series and seasonality and more. It offers statistical components of datasets, such as the variance and covariance.
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!
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 from Mathematics for Machine Learning and Data Science Specialization
Notes taken during studying mathematics and machine learning
Linear Algebra; Multivariate Calculus; Optimization; Probability and Statistics; Phenomena in High Dimensions; Approximation Theory; Functional Analysis, etc..
Repo contains miscellaneous programs
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