Udemy – Hyperparameter Optimization for Machine Learning 2021-5 – Download

Description

Hyperparameter Optimization for Machine Learning is a hyperparameter optimization course published by Udemy Academy. This course covers a number of topics, the most important of which are network search, random search, Bayesian optimization, multi-fidelity models, the Optuna framework, the Hyperopt library and Scikit-Optimize. East. And… underlined. In this training, he becomes familiar with the selection techniques to select the best and most optimal meta-parameter and is able to provide the performance of car models as much as possible. There are metaparameter optimization features that in this training course learn the pros and cons as well as the functional considerations of each.

What You’ll Learn in Hyperparameter Optimization for Machine Learning

  • Adjust and optimize the metaparameter and understand its importance and why
  • Cross-validation method
  • Adjusting and optimizing meta-parameters with network search and random and random search methods
  • Bayesian optimization
  • Optimization approach for tree-based Parzen estimators
  • Population-based training
  • Libraries and frameworks Hyperopt, Optuna, Scikit-optimize and Keras Turner

Course Specifications

Editor: Udemy
Instructors: Soledad Galli
French language
Intermediate level
Number of lessons: 94
Duration: 9 hours and 26 minutes

Course themes for 2022/3

Hyperparameter Optimization for Machine Learning Content

Optimizing Hyperparameters for Machine Learning Prerequisites

Python programming, including knowledge of NumPy, Pandas and Scikit-learn

Familiarity with basic machine learning algorithms, i.e. regression, support vector machines and nearest neighbors

Familiarity with decision tree algorithms and random forests

Familiarity with gradient boosting machines i.e. xgboost, lightGBM

Understanding machine learning model evaluation metrics

Familiarity with neural networks

Pictures

Hyperparameter Optimization for Machine Learning

Introductory video on hyperparameter optimization for machine learning

installation guide

After the clip, watch with your favorite reader.

english subtitles

Quality: 720p

Download links

Download Part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 1 GB

Download part 4 – 291 MB

File password(s): free download software

size

3.29 GB

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