vrdmr / CS273a-Introduction-to-Machine-LearningLinks
Introduction to machine learning and data mining  How can a machine learn from experience, to become better at a given task? How can we automatically extract knowledge or make sense of massive quantities of data? These are the fundamental questions of machine learning. Machine learning and data mining algorithms use techniques from statistics, o…
☆41Updated 10 years ago
Alternatives and similar repositories for CS273a-Introduction-to-Machine-Learning
Users that are interested in CS273a-Introduction-to-Machine-Learning are comparing it to the libraries listed below
Sorting:
- machine learning☆39Updated 7 years ago
 - Artificial Neural Networks - Gradient descent, BFGS, Regularization with Jupyter notebook☆65Updated 3 years ago
 - Heuristic Optimization for Python☆73Updated 5 years ago
 - Topics - Linear Regression, Logistic Regression, Regularization, Neural Networks, System Design, Support Vector Machines, Unsupervised Le…☆24Updated 7 years ago
 - This is the code for "Gaussian Mixture Models - The Math of Intelligence (Week 7)" By Siraj Raval on Youtube☆146Updated 6 years ago
 - An implementation of the Viterbi Algorithm for training Hidden Markov models. This repo accompanies the video found here: https://www.you…☆147Updated 3 years ago
 - Bayesian Deep Learning and Deep Reinforcement Learning for Object Shape Error Response and Correction of Manufacturing Systems☆44Updated 2 years ago
 - Slides and lecture notes for the course 'machine learning I' taught at the Graduate School Neural Information Processing in Tuebingen.☆30Updated 9 years ago
 - Using Genetic Algorithms to optimize Recurrent Neural Network's Configuration☆81Updated 8 years ago
 - Materials for "Bayesian Methods for Machine Learning" Coursera MOOC☆137Updated 5 years ago
 - YAGTOM: Yet Another Guide TO Matlab☆57Updated 11 years ago
 - Source Code for 'MATLAB Machine Learning Recipes' by Michael Paluszek and Stephanie Thomas☆55Updated 5 years ago
 - Source code for 'MATLAB Deep Learning' by Phil Kim☆100Updated last year
 - Code and data for the second edition of the textbook `Machine Learning: An Algorithm Perspective" by Stephen Marsland.☆149Updated 4 years ago
 - An IPython notebook showing the basics of implementing gradient descent and stochastic gradient descent in Python☆66Updated 2 years ago
 - Deep Learning application to the partial differential equations☆30Updated 7 years ago
 - Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.☆94Updated 4 years ago
 - PSO algorithm written in TensorFlow☆19Updated 6 years ago
 - Tuning the Parameters of Heuristic Optimizers (Meta-Optimization / Hyper-Parameter Optimization)☆56Updated 7 years ago
 - Anamoly Detection with Autoencoders - Credit Card Fraud Case☆16Updated 5 years ago
 - Mastering Machine Learning with scikit learn Second Edition, published by Packt☆81Updated 4 years ago
 - Deep learning for time-series data☆49Updated 2 years ago
 - A collection of black-box optimizers with a focus on evolutionary algorithms☆28Updated 5 years ago
 - Feature reduction using genetic algorithm☆25Updated 2 years ago
 - UNIVR PDE course project and just for fun☆117Updated 8 years ago
 - ☆135Updated 3 years ago
 - A MATLAB implementation of the TensorFlow Neural Networks Playground seen on http://playground.tensorflow.org/☆73Updated 8 years ago
 - This is the code for "K-Means Clustering - The Math of Intelligence (Week 3)" By SIraj Raval on Youtube☆125Updated 5 years ago
 - A simple example of how a genetic algorithm can be used to select the optimal subset of features to use for machine learning problems.☆69Updated 8 years ago
 - Using Imblearn To Tackle Imbalanced Data Sets☆37Updated 9 years ago