Playlist Duration

Playlist · sentdex

Machine Learning with Python

by sentdex · 72 videos

Listed in Best free machine learning courses on YouTube, ranked by total hours

Total watch time

18h 48m

at 1× speed · exactly 18 hours, 47 minutes, 30 seconds at 1×

At an hour a day you'd finish in 19 days

The shape of the course

72 videos in blocks of 10 · each column is a block's total, to scale

1h 40m
2h 3m
2h 48m
2h 45m
3h 39m
2h 53m
2h 19m
40m 17s

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Your plan

Plan to finish

About 19 days at an hour a day

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Days

At one hour a day, every day, this playlist takes about 19 days. Turn on JavaScript to plan around your week.

Videos (72)

18h 48m in total · tick what you've watched

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Videos to
Watched Leave out of the total
1 Practical Machine Learning Tutorial with Python Intro p.1 5:55 2016-04-11
2 Regression Intro - Practical Machine Learning Tutorial with Python p.2 10:58 2016-04-11
3 Regression Features and Labels - Practical Machine Learning Tutorial with Python p.3 10:17 2016-04-12
4 Regression Training and Testing - Practical Machine Learning Tutorial with Python p.4 16:26 2016-04-12
5 Regression forecasting and predicting - Practical Machine Learning Tutorial with Python p.5 14:28 2016-04-14
6 Pickling and Scaling - Practical Machine Learning Tutorial with Python p.6 6:25 2016-04-15
7 Regression How it Works - Practical Machine Learning Tutorial with Python p.7 7:57 2016-04-16
8 How to program the Best Fit Slope - Practical Machine Learning Tutorial with Python p.8 11:44 2016-04-17
9 How to program the Best Fit Line - Practical Machine Learning Tutorial with Python p.9 7:35 2016-04-18
10 R Squared Theory - Practical Machine Learning Tutorial with Python p.10 8:36 2016-04-21
11 Programming R Squared - Practical Machine Learning Tutorial with Python p.11 7:01 2016-04-23
12 Testing Assumptions - Practical Machine Learning Tutorial with Python p.12 20:33 2016-04-26
13 Classification w/ K Nearest Neighbors Intro - Practical Machine Learning Tutorial with Python p.13 11:11 2016-04-29
14 K Nearest Neighbors Application - Practical Machine Learning Tutorial with Python p.14 21:41 2016-05-01
15 Euclidean Distance - Practical Machine Learning Tutorial with Python p.15 6:53 2016-05-03
16 Creating Our K Nearest Neighbors Algorithm - Practical Machine Learning with Python p.16 9:15 2016-05-05
17 Writing our own K Nearest Neighbors in Code - Practical Machine Learning Tutorial with Python p.17 10:17 2016-05-06
18 Applying our K Nearest Neighbors Algorithm - Practical Machine Learning Tutorial with Python p.18 13:17 2016-05-09
19 Final thoughts on K Nearest Neighbors - Practical Machine Learning Tutorial with Python p.19 14:37 2016-05-11
20 Support Vector Machine Intro and Application - Practical Machine Learning Tutorial with Python p.20 8:31 2016-05-13
21 Understanding Vectors - Practical Machine Learning Tutorial with Python p.21 6:07 2016-05-16
22 Support Vector Assertion - Practical Machine Learning Tutorial with Python p.22 10:07 2016-05-17
23 Support Vector Machine Fundamentals - Practical Machine Learning Tutorial with Python p.23 15:35 2016-05-19
24 Support Vector Machine Optimization - Practical Machine Learning Tutorial with Python p.24 28:20 2016-05-21
25 Creating an SVM from scratch - Practical Machine Learning Tutorial with Python p.25 10:16 2016-05-23
26 SVM Training - Practical Machine Learning Tutorial with Python p.26 14:23 2016-05-24
27 SVM Optimization - Practical Machine Learning Tutorial with Python p.27 17:37 2016-05-26
28 Completing SVM from Scratch - Practical Machine Learning Tutorial with Python p.28 28:50 2016-05-28
29 Kernels Introduction - Practical Machine Learning Tutorial with Python p.29 15:22 2016-05-29
30 Why Kernels - Practical Machine Learning Tutorial with Python p.30 21:19 2016-05-30
31 Soft Margin SVM - Practical Machine Learning Tutorial with Python p.31 18:22 2016-05-31
32 Soft Margin SVM and Kernels with CVXOPT - Practical Machine Learning Tutorial with Python p.32 11:11 2016-06-01
33 SVM Parameters - Practical Machine Learning Tutorial with Python p.33 17:28 2016-06-02
34 Clustering Introduction - Practical Machine Learning Tutorial with Python p.34 20:15 2016-06-07
35 Handling Non-Numeric Data - Practical Machine Learning Tutorial with Python p.35 16:50 2016-06-10
36 K Means with Titanic Dataset - Practical Machine Learning Tutorial with Python p.36 17:09 2016-06-11
37 Custom K Means - Practical Machine Learning Tutorial with Python p.37 14:09 2016-06-20
38 K Means from Scratch - Practical Machine Learning Tutorial with Python p.38 14:59 2016-06-22
39 Mean Shift Intro - Practical Machine Learning Tutorial with Python p.39 11:42 2016-06-29
40 Mean Shift with Titanic Dataset - Practical Machine Learning Tutorial with Python p.40 22:48 2016-07-01
41 Mean Shift from Scratch - Practical Machine Learning Tutorial with Python p.41 17:27 2016-07-05
42 Mean Shift Dynamic Bandwidth - Practical Machine Learning Tutorial with Python p.42 29:22 2016-07-07
43 Deep Learning with Neural Networks and TensorFlow Introduction 22:33 2016-07-18
44 Installing TensorFlow (OPTIONAL) - Deep Learning with Neural Networks and TensorFlow p2.1 27:46 2016-07-18
45 TensorFlow Basics - Deep Learning with Neural Networks p. 2 15:50 2016-07-19
46 Neural Network Model - Deep Learning with Neural Networks and TensorFlow 32:51 2016-07-20
47 Running our Network - Deep Learning with Neural Networks and TensorFlow 25:15 2016-07-21
48 Processing our own Data - Deep Learning with Neural Networks and TensorFlow part 5 13:02 2016-08-22
49 Preprocessing cont'd - Deep Learning with Neural Networks and TensorFlow part 6 22:49 2016-08-23
50 Training/Testing on our Data - Deep Learning with Neural Networks and TensorFlow part 7 12:22 2016-08-24
51 Using More Data - Deep Learning with Neural Networks and TensorFlow part 8 25:13 2016-08-25
52 Installing the GPU version of TensorFlow for making use of your CUDA GPU 15:54 2016-08-26
53 Installing CPU and GPU TensorFlow on Windows 18:16 2016-12-11
54 Recurrent Neural Networks (RNN) - Deep Learning with Neural Networks and TensorFlow 10 12:38 2016-09-13
55 RNN Example in Tensorflow - Deep Learning with Neural Networks 11 14:20 2016-09-14
56 Convolutional Neural Networks Basics - Deep Learning withTensorFlow 12 9:11 2016-09-19
57 Convolutional Neural Networks with TensorFlow - Deep Learning with Neural Networks 13 25:07 2016-09-20
58 TFLearn - Deep Learning with Neural Networks and TensorFlow p. 14 27:42 2016-10-04
59 Intro - Training a neural network to play a game with TensorFlow and Open AI 12:32 2017-03-13
60 Training Data - Training a neural network to play a game with TensorFlow and Open AI p.2 12:07 2017-03-13
61 Training Model - Training a neural network to play a game with TensorFlow and Open AI p.3 14:38 2017-03-13
62 Testing Network - Training a neural network to play a game with TensorFlow and Open AI p.4 16:16 2017-03-13
63 Intro and preprocessing - Using Convolutional Neural Network to Identify Dogs vs Cats p. 1 12:51 2017-02-22
64 Building the Network - Using Convolutional Neural Network to Identify Dogs vs Cats p. 2 9:05 2017-02-22
65 Training - Using Convolutional Neural Network to Identify Dogs vs Cats p. 3 19:02 2017-02-22
66 Using our Network - Using Convolutional Neural Network to Identify Dogs vs Cats p. 4 10:51 2017-02-22
67 Introduction - 3D Convolutional Neural Network w/ Kaggle Lung Cancer Detection Competiton p.1 11:35 2017-02-10
68 Reading Files - 3D Convolutional Neural Network w/ Kaggle and 3D medical imaging p.2 20:55 2017-02-10
69 Visualizing - 3D Convolutional Neural Network w/ Kaggle and 3D medical imaging p.3 9:42 2017-02-10
70 Resizing Data - 3D Convolutional Neural Network w/ Kaggle and 3D medical imaging p.4 13:35 2017-02-10
71 Preprocessing data - 3D Convolutional Neural Network w/ Kaggle and 3D medical imaging p.5 10:55 2017-02-10
72 Running the Network - 3D Convolutional Neural Network w/ Kaggle and 3D medical imaging p.6 29:22 2017-02-10
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