Intro to Machine Learning & Data Science (+Pandas, NumPy, Matplotlib)

Video Description

Become a Machine Learning Engineer! Join Daniel Bourke & Andrei Neagoie as they take you from complete beginner to learning the basics of Machine Learning & Data Science. In this 10-hour beginner course, you'll learn: machine learning 101, environment setup, data analysis, and some popular ML libraries like Pandas, NumPy & Matplotlib! This Crash Course is ~25% of Andrei & Daniel's Machine Learning & Data Science Bootcamp course. So if you like this video, you'll LOVE their full course which has 30+ hours of additional lectures where you'll get to build your own machine learning models from scratch! Want to get hired as a professional ML Engineer or Data Scientist? Then take the full course 👇 🤖 Full Machine Learning & Data Science Bootcamp Course: https://zerotomastery.io/courses/machine-learning-and-data-science-bootcamp/ 🎁 [LIMITED TIME ONLY] Use code: YTMLDS10 to get 10% OFF (for life!) ========== 🗂 Crash Course Files: https://links.zerotomastery.io/machine-learning-crash-course 📓 Course Handbook: https://dev.mrdbourke.com/zero-to-mastery-ml/ 🐍 Free Python Crash Course: https://youtu.be/4uBbCUjJ_G8 ========== ⏲ Timestamps: 00:00 Course Intro 01:50 Your First Day 05:50 What Is Machine Learning? 12:54 AI/Machine Learning/Data Science 17:57 Exercise: Machine Learning Playground 24:25 How Did We Get Here? 30:40 Exercise: YouTube Recommendation Engine 35:18 Types of Machine Learning 40:11 What Is Machine Learning? Round 2 42:11 Section Review 47:08 Section Overview: Machine Learning and Data Science Framework 50:28 Introducing Our Framework 53:17 6-Step Machine Learning Framework 58:29 Types of Machine Learning Problems 1:09:13 Types of Data 1:14:16 Types of Evaluation 1:17:59 Features in Data 1:23:33 Modelling - Splitting Data 1:29:44 Modelling - Picking the Model 1:37:59 Modelling - Comparison 1:47:44 Overfitting and Underfitting Definitions: Experimentation 1:51:47 Tools We Will Use 1:55:59 Quick Announcement 1:57:04 Section Overview: Data Science Environment Setup 1:58:24 Introducing Our Tools 2:02:06 What is Conda? 2:04:52 Conda Environments 2:09:35 Mac Environment Setup 2:27:14 Mac Environment Setup 2 2:47:06 Windows Environment Setup 2 3:10:35 Linux Environment Setup 3:10:51 Sharing your Conda Environment 3:11:03 Jupyter Notebook Walkthrough 3:21:37 Jupyter Notebook Walkthrough 2 3:38:06 J upyter Notebook Walkthrough 3 3:46:28 Section Overview: Pandas - Data Analysis 3:49:08 Downloading Workbooks & Assignments - https://github.com/mrdbourke/zero-to-mastery-ml 3:49:19 Pandas Introduction 3:54:00 Series, Data Frames & CSVs 4:07:34 Data from URLs 4:07:45 Describing Data with Pandas 4:17:46 Selecting and Viewing Data with Pandas 4:29:07 Selecting and Viewing Data with Pandas Part 2 4:42:25 Manipulating Data 4:56:34 Manipulating Data 2 5:06:43 Manipulating Data 3 5:17:07 Assignment: Pandas Practice 5:17:18 How To Download The Course Assignments - https://github.com/mrdbourke/zero-to-mastery-ml 5:25:14 Section Overview: NumPy 5:28:06 NumPy Introduction 5:33:35 Quick Note: Correction in the next video 5:34:23 NumPy DataTypes and Attributes 5:48:40 Creating NumPy Arrays 5:58:15 NumPy Random Seed 6:05:43 Viewing Arrays and Matrices 6:15:33 Manipulating Arrays 6:27:16 Manipulating Arrays 2 6:37:11 Standard Deviation and Variance 6:44:34 Reshape and Transpose 6:52:12 Dot Product vs Element Wise 7:04:08 Exercise: Nut Butter Store Sales 7:17:24 Comparison Operators 7:21:10 Sorting Arrays 7:27:41 T urn Images Into NumPy Arrays 7:35:31 Assignment: NumPy Practice 7:35:42 Section Overview: Matplotlib - Plotting and Data Visualization 7:37:45 Matplotlib Introduction 7:43:14 Importing And Using Matplotlib 7:55:02 Anatomy Of A Matplotlib Figure 8:04:24 Scatter Plot And Bar Plot 8:14:45 Histograms And Subplots 8:23:37 Subplots Option 2 8:28:05 Quick Tip: Data Visualizations 8:34:15 Plotting From Pandas DataFrames 8:36:15 Quick Note: Regular Expressions 8:36:27 Plotting From Pandas DataFrames 2 8:47:13 Plotting from Pandas DataFrames 3 8:55:57 Plotting from Pandas DataFrames 4 9:02:44 Plotting from Pandas DataFrames 5 9:11:25 Plotting from Pandas DataFrames 6 9:20:06 Plotting from Pandas DataFrames 7 9:31:38 Customizing Your Plots 9:41:59 Customizing Your Plots 2 9:51:52 Saving And Sharing Your Plots 9:56:18 Assignment: Matplotlib Practice 9:56:30 Section Overview: Scikit-learn Creating Machine Learning Models 9:59:10 Where To Keep Learning ========== Graduates of Zero To Mastery are now working at Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, Shopify + other top tech companies. Many are also working as top-rated Freelancers getting paid $1,000s while working remotely around the world. 🎓 Here are just a few of them: https://zerotomastery.io/testimonials This could be you 👆 ========== Full ML Bootcamp 👉 https://zerotomastery.io/courses/machine-learning-and-data-science-bootcamp/ #zerotomastery #machinelearning