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| 10 - Ch2 Validating the model.m4v |
6.71Мб |
| 11 - Ch2 Regularization.m4v |
4.04Мб |
| 12 - Ch2 Using the model.m4v |
3.69Мб |
| 13 - Ch3 Machine learning for classification.m4v |
6.26Мб |
| 14 - Ch3 Initial data preparation.m4v |
5.30Мб |
| 15 - Ch3 Feature importance, Part 1.m4v |
5.44Мб |
| 16 - Ch3 Feature importance, Part 2.m4v |
3.95Мб |
| 17 - Ch3 Feature engineering.m4v |
4.27Мб |
| 18 - Ch3 Machine learning for classification.m4v |
3.22Мб |
| 19 - Ch3 Training logistic regression.m4v |
5.17Мб |
| 1 - Ch1 Introduction to machine learning.m4v |
6.65Мб |
| 20 - Ch3 Model interpretation.m4v |
6.46Мб |
| 21 - Ch3 Using the model.m4v |
6.21Мб |
| 22 - Ch4 Evaluation metrics for classification.m4v |
5.60Мб |
| 23 - Ch4 Confusion table.m4v |
5.76Мб |
| 24 - Ch4 Precision and recall.m4v |
3.16Мб |
| 25 - Ch4 ROC curve and AUC score.m4v |
6.83Мб |
| 26 - Ch4 ROC Curve.m4v |
5.89Мб |
| 27 - Ch4 Parameter tuning.m4v |
3.61Мб |
| 28 - Ch4 Next steps.m4v |
5.67Мб |
| 29 - Ch 5 Deploying machine learning models.m4v |
4.53Мб |
| 2 - Ch1 When machine learning isn’t helpful.m4v |
6.47Мб |
| 30 - Ch5 Model serving.m4v |
5.40Мб |
| 31 - Ch5 Managing dependencies.m4v |
4.15Мб |
| 32 - Ch5 Docker.m4v |
3.63Мб |
| 33 - Ch5 Deployment.m4v |
4.89Мб |
| 34 - Ch6 Decision trees and ensemble learning.m4v |
3.07Мб |
| 35 - Ch6 Data cleaning.m4v |
5.43Мб |
| 36 - Ch6 Decision trees.m4v |
5.38Мб |
| 37 - Ch6 Decision tree learning algorithm.m4v |
4.58Мб |
| 38 - Ch6 Random forest.m4v |
4.29Мб |
| 39 - Ch6 Gradient boosting.m4v |
3.51Мб |
| 3 - Ch1 Evaluation.m4v |
6.02Мб |
| 40 - Ch6 Parameter tuning for XGBoost.m4v |
6.24Мб |
| 41 - Ch6 Next steps.m4v |
3.92Мб |
| 42 - Ch7 Neural networks and deep learning.m4v |
5.80Мб |
| 43 - Ch7 Convolutional neural networks.m4v |
3.21Мб |
| 44 - Ch7 Internals of the model.m4v |
3.47Мб |
| 45 - Ch7 Training the model.m4v |
3.71Мб |
| 46 - Ch7 Training the model - again.m4v |
4.57Мб |
| 47 - Ch7 Saving the model and checkpointing.m4v |
5.39Мб |
| 48 - Ch7 Data augmentation.m4v |
4.58Мб |
| 49 - Ch7 Using the model.m4v |
5.73Мб |
| 4 - Ch2 Machine learning for regression.m4v |
3.84Мб |
| 50 - Ch8 Serverless deep learning.m4v |
6.59Мб |
| 51 - Ch8 Preparing the Docker image.m4v |
6.73Мб |
| 52 - Ch9 Serving models with Kubernetes and Kubeflow.m4v |
5.53Мб |
| 53 - Ch9 Running TensorFlow Serving locally.m4v |
6.53Мб |
| 54 - Ch9 Model deployment with Kubernetes.m4v |
6.35Мб |
| 55 - Ch9 Deploying to Kubernetes.m4v |
5.51Мб |
| 56 - Ch9 Model deployment with Kubeflow.m4v |
3.82Мб |
| 57 - Ch9 KFServing transformers.m4v |
4.66Мб |
| 5 - Ch2 Exploratory data analysis.m4v |
4.52Мб |
| 6 - Ch2 Target variable analysis.m4v |
4.87Мб |
| 7 - Ch2 Machine learning for regression - again.m4v |
5.36Мб |
| 8 - Ch2 Linear regression.m4v |
4.77Мб |
| 9 - Ch2 Predicting the price.m4v |
5.24Мб |
| Manning.Machine.learning.bookcamp.2021.pdf |
9.91Мб |