Machine Learning Book camp Video Edition
Focused View
8:59:20
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1 - Chapter 1 Introduction to machine learning.mp4
12:39
2 - Chapter 1 When machine learning isnt helpful.mp4
11:32
3 - Chapter 1 Evaluation.mp4
11:22
4 - Chapter 2 Machine learning for regression.mp4
06:43
5 - Chapter 2 Exploratory data analysis.mp4
08:25
6 - Chapter 2 Target variable analysis.mp4
09:35
7 - Chapter 2 Machine learning for regression - again.mp4
10:24
8 - Chapter 2 Linear regression.mp4
09:35
9 - Chapter 2 Predicting the price.mp4
10:18
10 - Chapter 2 Validating the model.mp4
12:20
11 - Chapter 2 Regularization.mp4
07:35
12 - Chapter 2 Using the model.mp4
06:07
13 - Chapter 3 Machine learning for classification.mp4
11:24
14 - Chapter 3 Initial data preparation.mp4
10:37
15 - Chapter 3 Feature importance, Part 1.mp4
09:53
16 - Chapter 3 Feature importance, Part 2.mp4
06:45
17 - Chapter 3 Feature engineering.mp4
08:02
18 - Chapter 3 Machine learning for classification.mp4
06:05
19 - Chapter 3 Training logistic regression.mp4
10:10
20 - Chapter 3 Model interpretation.mp4
12:37
21 - Chapter 3 Using the model.mp4
10:05
22 - Chapter 4 Evaluation metrics for classification.mp4
10:28
23 - Chapter 4 Confusion table.mp4
11:07
24 - Chapter 4 Precision and recall.mp4
06:07
25 - Chapter 4 ROC curve and AUC score.mp4
12:46
26 - Chapter 4 ROC Curve.mp4
11:07
27 - Chapter 4 Parameter tuning.mp4
06:43
28 - Chapter 4 Next steps.mp4
08:08
29 - Chapter 5 Deploying machine learning models.mp4
08:51
30 - Chapter 5 Model serving.mp4
10:55
31 - Chapter 5 Managing dependencies.mp4
08:22
32 - Chapter 5 Docker.mp4
07:10
33 - Chapter 5 Deployment.mp4
09:12
34 - Chapter 6 Decision trees and ensemble learning.mp4
05:32
35 - Chapter 6 Data cleaning.mp4
10:34
36 - Chapter 6 Decision trees.mp4
10:35
37 - Chapter 6 Decision tree learning algorithm.mp4
08:56
38 - Chapter 6 Random forest.mp4
08:28
39 - Chapter 6 Gradient boosting.mp4
06:55
40 - Chapter 6 Parameter tuning for XGBoost.mp4
11:59
41 - Chapter 6 Next steps.mp4
06:12
42 - Chapter 7 Neural networks and deep learning.mp4
10:53
43 - Chapter 7 Convolutional neural networks.mp4
06:31
44 - Chapter 7 Internals of the model.mp4
07:05
45 - Chapter 7 Training the model.mp4
07:31
46 - Chapter 7 Training the model - again.mp4
08:55
47 - Chapter 7 Saving the model and checkpointing.mp4
10:22
48 - Chapter 7 Data augmentation.mp4
08:48
49 - Chapter 7 Using the model.mp4
10:11
50 - Chapter 8 Serverless deep learning.mp4
12:42
51 - Chapter 8 Preparing the Docker image.mp4
12:57
52 - Chapter 9 Serving models with Kubernetes and Kubeflow.mp4
10:18
53 - Chapter 9 Running TensorFlow Serving locally.mp4
12:25
54 - Chapter 9 Model deployment with Kubernetes.mp4
12:12
55 - Chapter 9 Deploying to Kubernetes.mp4
10:30
56 - Chapter 9 Model deployment with Kubeflow.mp4
07:22
57 - Chapter 9 KFServing transformers.mp4
08:18
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O'Reilly
View courses O'ReillyO'Reilly Media is an American learning company established by Tim O'Reilly that publishes books, produces tech conferences, and provides an online learning platform. Its distinctive brand features a woodcut of an animal on many of its book covers.
- language english
- Training sessions 57
- duration 8:59:20
- Release Date 2023/11/06
