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[Manning] Machine learning bookcamp (hevc) (2021) [EN]
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2023-8-25 20:19
2024-12-26 10:02
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286.19 MB
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磁力链接
magnet:?xt=urn:btih:63ab46b6e621e43ea1b690108b1b949229fd4c42
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOjYzYWI0NmI2ZTYyMWU0M2VhMWI2OTAxMDhiMWI5NDkyMjlmZDRjNDJaWg==
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相关链接
Manning
Machine
learning
bookcamp
hevc
2021
EN
文件列表
1 - Ch1 Introduction to machine learning.m4v
6.65MB
2 - Ch1 When machine learning isn’t helpful.m4v
6.47MB
3 - Ch1 Evaluation.m4v
6.02MB
4 - Ch2 Machine learning for regression.m4v
3.84MB
5 - Ch2 Exploratory data analysis.m4v
4.52MB
6 - Ch2 Target variable analysis.m4v
4.87MB
7 - Ch2 Machine learning for regression - again.m4v
5.36MB
8 - Ch2 Linear regression.m4v
4.77MB
9 - Ch2 Predicting the price.m4v
5.24MB
10 - Ch2 Validating the model.m4v
6.71MB
11 - Ch2 Regularization.m4v
4.04MB
12 - Ch2 Using the model.m4v
3.69MB
13 - Ch3 Machine learning for classification.m4v
6.26MB
14 - Ch3 Initial data preparation.m4v
5.3MB
15 - Ch3 Feature importance, Part 1.m4v
5.44MB
16 - Ch3 Feature importance, Part 2.m4v
3.95MB
17 - Ch3 Feature engineering.m4v
4.27MB
18 - Ch3 Machine learning for classification.m4v
3.22MB
19 - Ch3 Training logistic regression.m4v
5.17MB
20 - Ch3 Model interpretation.m4v
6.46MB
21 - Ch3 Using the model.m4v
6.21MB
22 - Ch4 Evaluation metrics for classification.m4v
5.6MB
23 - Ch4 Confusion table.m4v
5.76MB
24 - Ch4 Precision and recall.m4v
3.16MB
25 - Ch4 ROC curve and AUC score.m4v
6.83MB
26 - Ch4 ROC Curve.m4v
5.89MB
27 - Ch4 Parameter tuning.m4v
3.61MB
28 - Ch4 Next steps.m4v
5.67MB
29 - Ch 5 Deploying machine learning models.m4v
4.53MB
30 - Ch5 Model serving.m4v
5.4MB
31 - Ch5 Managing dependencies.m4v
4.15MB
32 - Ch5 Docker.m4v
3.63MB
33 - Ch5 Deployment.m4v
4.89MB
34 - Ch6 Decision trees and ensemble learning.m4v
3.07MB
35 - Ch6 Data cleaning.m4v
5.43MB
36 - Ch6 Decision trees.m4v
5.38MB
37 - Ch6 Decision tree learning algorithm.m4v
4.58MB
38 - Ch6 Random forest.m4v
4.29MB
39 - Ch6 Gradient boosting.m4v
3.51MB
40 - Ch6 Parameter tuning for XGBoost.m4v
6.24MB
41 - Ch6 Next steps.m4v
3.92MB
42 - Ch7 Neural networks and deep learning.m4v
5.8MB
43 - Ch7 Convolutional neural networks.m4v
3.21MB
44 - Ch7 Internals of the model.m4v
3.47MB
45 - Ch7 Training the model.m4v
3.71MB
46 - Ch7 Training the model - again.m4v
4.57MB
47 - Ch7 Saving the model and checkpointing.m4v
5.39MB
48 - Ch7 Data augmentation.m4v
4.58MB
49 - Ch7 Using the model.m4v
5.73MB
50 - Ch8 Serverless deep learning.m4v
6.59MB
51 - Ch8 Preparing the Docker image.m4v
6.73MB
52 - Ch9 Serving models with Kubernetes and Kubeflow.m4v
5.53MB
53 - Ch9 Running TensorFlow Serving locally.m4v
6.53MB
54 - Ch9 Model deployment with Kubernetes.m4v
6.35MB
55 - Ch9 Deploying to Kubernetes.m4v
5.51MB
56 - Ch9 Model deployment with Kubeflow.m4v
3.82MB
57 - Ch9 KFServing transformers.m4v
4.66MB
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