All course materials for the Zero to Mastery Machine Learning and Data Science course.

Last update: Jan 08, 2023

Related tags

Deep Learning data-science machine-learning deep-learning

Overview

Zero to Mastery Machine Learning

Welcome! This repository contains all of the code, notebooks, images and other materials related to the Zero to Mastery Machine Learning Course on Udemy and zerotomastery.io.

If you'd like to see anything in particular, please send me an email: [email protected] or leave an issue.

What this course focuses on

Create a framework for working through problems (6 step machine learning modelling framework)
Find tools to fit the framework
Targeted practice = use tools and framework steps to work on end-to-end machine learning modelling projects

How this course is structured

Section 1 - Getting your mind and computer ready for machine learning (concepts, computer setup)
Section 2 - Tools for machine learning and data science (pandas, NumPy, Matplotlib, Scikit-Learn)
Section 3 - End-to-end structured data projects (classification and regression)
Section 4 - Neural networks, deep learning and transfer learning with TensorFlow 2.0
Section 5 - Communicating and sharing your work

Student notes

Some students have taken and shared extensive notes on this course, see them below.

If you'd like to submit yours, leave a pull request.

Chester's notes - https://github.com/chesterheng/machinelearning-datascience
Sophia's notes - https://www.rockyourcode.com/tags/udemy-complete-machine-learning-and-data-science-zero-to-mastery/

Owner

Daniel Bourke

Machine Learning Engineer live on YouTube.

Daniel Bourke

GitHub Repository https://dbourke.link/ZTMmlcourse

Bringing sanity to world of messed-up data

Sanitize sanitize is a Python module for making sure various things (e.g. HTML) are safe to use. It was originally written by Mark Pilgrim and is dist

63 Oct 26, 2021

Dogs classification with Deep Metric Learning using some popular losses

Tsinghua Dogs classification with Deep Metric Learning 1. Introduction Tsinghua Dogs dataset Tsinghua Dogs is a fine-grained classification dataset fo

45 Nov 09, 2022

(IEEE TIP 2021) Regularized Densely-connected Pyramid Network for Salient Instance Segmentation

RDPNet IEEE TIP 2021: Regularized Densely-connected Pyramid Network for Salient Instance Segmentation PyTorch training and testing code are available.

41 Oct 21, 2022

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

ALBERT ***************New March 28, 2020 *************** Add a colab tutorial to run fine-tuning for GLUE datasets. ***************New January 7, 2020

3k Jan 01, 2023

Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images

Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the

163 Sep 21, 2022

Datasets for new state-of-the-art challenge in disentanglement learning

High resolution disentanglement datasets This repository contains the Falcor3D and Isaac3D datasets, which present a state-of-the-art challenge for co

37 May 26, 2022

In this project, we'll be making our own screen recorder in Python using some libraries.

Screen Recorder in Python Project Description: In this project, we'll be making our own screen recorder in Python using some libraries. Requirements:

4 Jan 24, 2022

GB-CosFace: Rethinking Softmax-based Face Recognition from the Perspective of Open Set Classification

GB-CosFace: Rethinking Softmax-based Face Recognition from the Perspective of Open Set Classification This is the official pytorch implementation of t

5 Nov 14, 2022

Semantic Bottleneck Scene Generation

SB-GAN Semantic Bottleneck Scene Generation Coupling the high-fidelity generation capabilities of label-conditional image synthesis methods with the f

41 Nov 28, 2022

Unofficial implementation of Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segmentation

Point-Unet This is an unofficial implementation of the MICCAI 2021 paper Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segment

9 Dec 07, 2022

Open & Efficient for Framework for Aspect-based Sentiment Analysis

PyABSA - Open & Efficient for Framework for Aspect-based Sentiment Analysis Fast & Low Memory requirement & Enhanced implementation of Local Context F

567 Jan 07, 2023

Seeing if I can put together an interactive version of 3b1b's Manim in Streamlit

streamlit-manim Seeing if I can put together an interactive version of 3b1b's Manim in Streamlit Installation I had to install pango with sudo apt-get

6 Aug 03, 2022

Greedy Gaussian Segmentation

GGS Greedy Gaussian Segmentation (GGS) is a Python solver for efficiently segmenting multivariate time series data. For implementation details, please

72 Dec 07, 2022

The GitHub repository for the paper: “Time Series is a Special Sequence: Forecasting with Sample Convolution and Interaction“.

SCINet This is the original PyTorch implementation of the following work: Time Series is a Special Sequence: Forecasting with Sample Convolution and I

386 Jan 01, 2023

Easy to use Audio Tagging in PyTorch

Audio Classification, Tagging & Sound Event Detection in PyTorch Progress: Fine-tune on audio classification Fine-tune on audio tagging Fine-tune on s

15 Dec 22, 2022

MazeRL is an application oriented Deep Reinforcement Learning (RL) framework

MazeRL is an application oriented Deep Reinforcement Learning (RL) framework, addressing real-world decision problems. Our vision is to cover the complete development life cycle of RL applications ra

222 Dec 24, 2022

PyTorch implementation of DreamerV2 model-based RL algorithm

PyDreamer Reimplementation of DreamerV2 model-based RL algorithm in PyTorch. The official DreamerV2 implementation can be found here. Features ... Run

118 Dec 15, 2022

This is a collection of our NAS and Vision Transformer work.

AutoML - Neural Architecture Search This is a collection of our AutoML-NAS work iRPE (NEW): Rethinking and Improving Relative Position Encoding for Vi

832 Jan 08, 2023

Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis

Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis. You write a high level configuration file specifying your in

917 Jan 03, 2023

Sound and Cost-effective Fuzzing of Stripped Binaries by Incremental and Stochastic Rewriting

StochFuzz: A New Solution for Binary-only Fuzzing StochFuzz is a (probabilistically) sound and cost-effective fuzzing technique for stripped binaries.

164 Dec 05, 2022