Code and files to go along with CS329s machine learning model deployment tutorial.
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Updated
Nov 12, 2022 - Jupyter Notebook
Code and files to go along with CS329s machine learning model deployment tutorial.
Machine learning notes that make your reading easy
Text clustering with K-means and tf-idf
Classify movie posters by genre
♂️♀️ Detect a person's gender from a voice file (90.7% +/- 1.3% accuracy).
An example project that predicts house prices for a Kaggle competition using a Gradient Boosted Machine.
An example project using a feed-forward neural network for text sentiment classification trained with 25,000 movie reviews from the IMDB website.
Use the K Nearest Neighbors algorithm to predict the probability of a divorce with high accuracy.
An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.
Use the famous CIFAR-10 dataset to train a multi-layer neural network to recognize images of cats, dogs, and other things.
The original lightweight introduction to machine learning in Rubix ML using the famous Iris dataset and the K Nearest Neighbors classifier.
Handwritten digit recognizer using a feed-forward neural network and the MNIST dataset of 70,000 human-labeled handwritten digits.
Recognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.
Machine Learning tutorials covering both traditional and deep learning models.
Workshop on Deep Learning for Health and Life Sciences
The repository contains exercises on Machine Learning algorithms in R, using RStudio. Used to dive into ML, data preprocessing, data visualisation, and data exploration.
Supports de la conférence "Machine Learning pour tous avec python" présentée au Breizhcamp 2019
Build a classifier to predict the outcome of Dota 2 games with the Naive Bayes algorithm and results from 102,944 sample games.
Predict diabetes disease using a Logistic Regression with TensorFlow.js
Demonstrating unsupervised clustering using the K Means algorithm and synthetic color data.
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