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

Overview

Zero to Mastery Machine Learning

Binder Deepnote Colab

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

  1. Create a framework for working through problems (6 step machine learning modelling framework)
  2. Find tools to fit the framework
  3. 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.

  1. Chester's notes - https://github.com/chesterheng/machinelearning-datascience
  2. 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
Pytorch implementation for A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose

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Shih-Yang Su 172 Dec 22, 2022
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models

PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models This repository is the official implementation of the fol

DistributedML 41 Dec 06, 2022
The reference baseline of final exam for XMU machine learning course

Mini-NICO Baseline The baseline is a reference method for the final exam of machine learning course. Requirements Installation we use /python3.7 /torc

JoaquinChou 3 Dec 29, 2021
Generating synthetic mobility data for a realistic population with RNNs to improve utility and privacy

lbs-data Motivation Location data is collected from the public by private firms via mobile devices. Can this data also be used to serve the public goo

Alex 11 Sep 22, 2022
Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness

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CMU Locus Lab 36 Dec 30, 2022
codes for Image Inpainting with External-internal Learning and Monochromic Bottleneck

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97 Nov 29, 2022
Anagram Generator in Python

Anagrams Generator This is a program for computing multiword anagrams. It makes no effort to come up with sentences that make sense; it only finds ana

Day Fundora 5 Nov 17, 2022
Train Dense Passage Retriever (DPR) with a single GPU

Gradient Cached Dense Passage Retrieval Gradient Cached Dense Passage Retrieval (GC-DPR) - is an extension of the original DPR library. We introduce G

Luyu Gao 92 Jan 02, 2023
Neural Koopman Lyapunov Control

Neural-Koopman-Lyapunov-Control Code for our paper: Neural Koopman Lyapunov Control Requirements dReal4: v4.19.02.1 PyTorch: 1.2.0 The learning framew

Vrushabh Zinage 6 Dec 24, 2022
Official PyTorch implementation of Learning Intra-Batch Connections for Deep Metric Learning (ICML 2021) published at International Conference on Machine Learning

About This repository the official PyTorch implementation of Learning Intra-Batch Connections for Deep Metric Learning. The config files contain the s

Dynamic Vision and Learning Group 41 Dec 10, 2022
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018

Adversarial Learning for Semi-supervised Semantic Segmentation This repo is the pytorch implementation of the following paper: Adversarial Learning fo

Wayne Hung 464 Dec 19, 2022
The Few-Shot Bot: Prompt-Based Learning for Dialogue Systems

Few-Shot Bot: Prompt-Based Learning for Dialogue Systems This repository includes the dataset, experiments results, and code for the paper: Few-Shot B

Andrea Madotto 103 Dec 28, 2022
RCD: Relation Map Driven Cognitive Diagnosis for Intelligent Education Systems

RCD: Relation Map Driven Cognitive Diagnosis for Intelligent Education Systems This is our implementation for the paper: Weibo Gao, Qi Liu*, Zhenya Hu

BigData Lab @USTC 中科大大数据实验室 10 Oct 16, 2022
VOneNet: CNNs with a Primary Visual Cortex Front-End

VOneNet: CNNs with a Primary Visual Cortex Front-End A family of biologically-inspired Convolutional Neural Networks (CNNs). VOneNets have the followi

The DiCarlo Lab at MIT 99 Dec 22, 2022
Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.

Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.

Troyanskaya Laboratory 323 Jan 01, 2023
Code for our paper "Graph Pre-training for AMR Parsing and Generation" in ACL2022

AMRBART An implementation for ACL2022 paper "Graph Pre-training for AMR Parsing and Generation". You may find our paper here (Arxiv). Requirements pyt

xfbai 60 Jan 03, 2023
Semantic segmentation models, datasets and losses implemented in PyTorch.

Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm

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Implementation of CVPR 2020 Dual Super-Resolution Learning for Semantic Segmentation

Dual super-resolution learning for semantic segmentation 2021-01-02 Subpixel Update Happy new year! The 2020-12-29 update of SISR with subpixel conv p

Sam 79 Nov 24, 2022
NNR conformation conditional and global probabilities estimation and analysis in peptides or proteins fragments

NNR and global probabilities estimation and analysis in peptides or protein fragments This module calculates global and NNR conformation dependent pro

0 Jul 15, 2021
Implementation of gaze tracking and demo

Predicting Customer Demand by Using Gaze Detecting and Object Tracking This project is the integration of gaze detecting and object tracking. Predict

2 Oct 20, 2022