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/
Comments
  • I got an errors when I was trying to do data preprocessing

    I got an errors when I was trying to do data preprocessing

    I was trying to follow your steps to convert the categorical features in the car_sales dataframe to numbers but got some errors

    This is the thread: https://github.com/scikit-learn/scikit-learn/issues/17741

    opened by Blessing988 2
  • Update introduction-to-pandas notebook: typos and unfound bugs

    Update introduction-to-pandas notebook: typos and unfound bugs

    Here is my changes detail to introduction-to-pandas notebook:

    • Typos (aniamls -> animals, car_sales_missening -> car_sales_missing)
    • Change call column car_sales[“Odometer”] (can not found the column) to “car_sales[“Odometer (KM)”] ”
    • Change path in pd.read_csv("car-sales-missing-data.csv") (not found directory) to “../data/car-sales-missing-data.csv”

    Love your course ^^

    opened by mtosity 1
  • [Deleted] Update introduction-to-pandas notebook: typos and unfound bugs

    [Deleted] Update introduction-to-pandas notebook: typos and unfound bugs

    Here is my changes detail to introduction-to-pandas notebook:

    • Typos (animals, car_sales_missing)
    • Change call column “Odometer” (can not found column) to “Odometer (KM)”
    • Change path in pd.read_csv("car-sales-missing-data.csv") (not found) to “../data/car-sales…”

    Love your course ^^

    opened by mtosity 1
  • Add links to launch repo in Binder, Colab & Deepnote

    Add links to launch repo in Binder, Colab & Deepnote

    As seen on Aurélien Geron's Hands-On ML repo (https://github.com/ageron/handson-ml2), I have added links to launch the repo in Google Colab, Binder and Deepnote

    opened by jaintj95 1
  • Fixed the typo - xlabel and ylabel were interchanged for the bar plot in matplotlib exercise's solution

    Fixed the typo - xlabel and ylabel were interchanged for the bar plot in matplotlib exercise's solution

    Hey, I just noticed that the labels were interchanged for a bar plot in matplotlib exercise solutions. I know it's not really a big deal, just wanted to contribute :)

    opened by pavanskipo 1
  • fix: make use of functions parameters instead of global variables

    fix: make use of functions parameters instead of global variables

    Hi Daniel @mrdbourke

    I am sending this PR as a follow up to my couple of comments on your amazing Udemy course.

    As you have noticed, two functions in the course are passed parameters they never use, relying instead on global variables. This pull request help fix the issue by replacing the global variables with the proper function parameters.

    I am really enjoying the course and looking for more content from you in the future.

    Cheers Younes

    opened by youneshenniwrites 1
  • fixed recall definition

    fixed recall definition

    Fixed recall definition in end-to-end-hearth-disease-classification. There was a typo stating that the formula is TP / (TP + FP). This should be TP / (TP + FN)

    opened by Matus-Dubrava 1
  • Avoid adding cents in Price column

    Avoid adding cents in Price column

    While converting Price column into Int, cents are appended and get converted into whole integer. $4000.00 -> 400000

    After the suggested change, $4000.00 -> 4000

    opened by SaketMunda 0
  • Fix Sklearn version upgrades videos/code

    Fix Sklearn version upgrades videos/code

    Some students are getting different results when running different models in Scikit-Learn.

    This is because of different version upgrades (e.g. Scikit-Learn 0.23.0 -> 1.0.0).

    Find the videos/code that is showing the worst results and update them with the newer versions.

    opened by mrdbourke 1
Owner
Daniel Bourke
Machine Learning Engineer live on YouTube.
Daniel Bourke
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

Modeling High-Frequency Limit Order Book Dynamics Using Machine Learning Framework to capture the dynamics of high-frequency limit order books. Overvi

Chang-Shu Chung 1.3k Jan 7, 2023
This repository contains all the code and materials distributed in the 2021 Q-Programming Summer of Qode.

Q-Programming Summer of Qode This repository contains all the code and materials distributed in the Q-Programming Summer of Qode. If you want to creat

Sammarth Kumar 11 Jun 11, 2021
Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).

Adaptive Segmentation Mask Attack This repository contains the implementation of the Adaptive Segmentation Mask Attack (ASMA), a targeted adversarial

Utku Ozbulak 53 Jul 4, 2022
Useful materials and tutorials for 110-1 NTU DBME5028 (Application of Deep Learning in Medical Imaging)

Useful materials and tutorials for 110-1 NTU DBME5028 (Application of Deep Learning in Medical Imaging)

null 7 Jun 22, 2022
Computer Vision Script to recognize first person motion, developed as final project for the course "Machine Learning and Deep Learning"

Overview of The Code BaseColab/MLDL_FPAR.pdf: it contains the full explanation of our work Base Colab: it contains the base colab used to perform all

Simone Papicchio 4 Jul 16, 2022
Code for the AAAI 2022 paper "Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph".

multilingual-mrc-isdg Code for the AAAI 2022 paper "Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph". This r

Liyan 5 Dec 7, 2022
Bachelor's Thesis in Computer Science: Privacy-Preserving Federated Learning Applied to Decentralized Data

federated is the source code for the Bachelor's Thesis Privacy-Preserving Federated Learning Applied to Decentralized Data (Spring 2021, NTNU) Federat

Dilawar Mahmood 25 Nov 30, 2022
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

Machine Learning From Scratch About Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose

Erik Linder-Norén 21.8k Jan 9, 2023
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

This is the Vowpal Wabbit fast online learning code. Why Vowpal Wabbit? Vowpal Wabbit is a machine learning system which pushes the frontier of machin

Vowpal Wabbit 8.1k Jan 6, 2023
Official code for the CVPR 2022 (oral) paper "Extracting Triangular 3D Models, Materials, and Lighting From Images".

nvdiffrec Joint optimization of topology, materials and lighting from multi-view image observations as described in the paper Extracting Triangular 3D

NVIDIA Research Projects 1.4k Jan 1, 2023
code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning" by Zhongzheng Ren*, Raymond A. Yeh*, Alexander G. Schwing.

Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning Overview This code is for paper: Not All Unlabeled Data are Equa

Jason Ren 22 Nov 23, 2022
This repo contains research materials released by members of the Google Brain team in Tokyo.

Brain Tokyo Workshop ?? ?? This repo contains research materials released by members of the Google Brain team in Tokyo. Past Projects Weight Agnostic

Google 1.2k Jan 2, 2023
The materials used in the SaxonJS tutorial presented at Declarative Amsterdam, 2021

SaxonJS-Tutorial-2021, version 1.0.4 Last updated on 4 November, 2021. Table of contents Background Prerequisites Starting a web server Running a Java

Saxonica 11 Oct 23, 2022
An SE(3)-invariant autoencoder for generating the periodic structure of materials

Crystal Diffusion Variational AutoEncoder This software implementes Crystal Diffusion Variational AutoEncoder (CDVAE), which generates the periodic st

Tian Xie 94 Dec 10, 2022
Workshop Materials Delivered on 28/02/2022

intro-to-cnn-p1 Repo for hosting workshop materials delivered on 28/02/2022 Questions you will answer in this workshop Learning Objectives What are co

Beginners Machine Learning 5 Feb 28, 2022
The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding.

SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you

Yu Meng 38 Dec 12, 2022
A Peer-to-peer Platform for Secure, Privacy-preserving, Decentralized Data Science

PyGrid is a peer-to-peer network of data owners and data scientists who can collectively train AI models using PySyft. PyGrid is also the central serv

OpenMined 615 Jan 3, 2023