Hyperparameter Optimization for Machine Learning

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Nome:	Hyperparameter Optimization for Machine Learning
Descrizione: Description Welcome to Hyperparameter Optimization for Machine Learning. In this course, you will learn multiple techniques to select the best hyperparameters and improve the performance of your machine learning models. If you are regularly training machine learning models as a hobby or for your organization and want to improve the performance of your models, if you are keen to jump up in the leader board of a data science competition, or you simply want to learn more about how to tune hyperparameters of machine learning models, this course will show you how. We’ll take you step-by-step through engaging video tutorials and teach you everything you need to know about hyperparameter tuning. Throughout this comprehensive course, we cover almost every available approach to optimize hyperparameters, discussing their rationale, their advantages and shortcomings, the considerations to have when using the technique and their implementation in Python. Specifically, you will learn: What hyperparameters are and why tuning matters The use of cross-validation and nested cross-validation for optimization Grid search and Random search for hyperparameters Bayesian Optimization Tree-structured Parzen estimators SMAC, Population Based Optimization and other SMBO algorithms How to implement these techniques with available open source packages including Hyperopt, Optuna, Scikit-optimize, Keras Turner and others. By the end of the course, you will be able to decide which approach you would like to follow and carry it out with available open-source libraries. This comprehensive machine learning course includes over 50 lectures spanning about 8 hours of video, and ALL topics include hands-on Python code examples which you can use for reference and for practice, and re-use in your own projects. So what are you waiting for? Enroll today, learn how to tune the hyperparameters of your models and build better machine learning models. Who this course is for: Students who want to know more about hyperparameter optimization algorithms Students who want to understand advanced techniques for hyperparameter optimization Students who want to learn to use multiple open source libraries for hyperparameter tuning Students interested in building better performing machine learning models Students interested in participating in data science competitions Students seeking to expand their breadth of knowledge on machine learning Requirements Python programming, including knowledge of NumPy, Pandas and Scikit-learn Familiarity with basic machine learning algorithms, i.e., regression, support vector machines and nearest neighbours Familiarity with decision tree algorithms and Random Forests Familiarity with gradient boosting machines, i.e., xgboost, lightGBMs Understanding of machine learning model evaluation metrics Familiarity with Neuronal Networks Last Updated 5/2021
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Categoria:	Tutorials
Lingua:	English
Dimensione totale:	2.92 GB
Info Hash:	E4212AF849E28F20B19D6AE5025E0057494D2F2F
Aggiunto di:	tutsnode
Data di aggiunta:	2021-06-07 13:35:59
Stato torrent:	Torrent Verified

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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/001 Introduction.en.srt	4.33 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/001 Introduction.mp4	61.72 MB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/002 Course Curriculum.en.srt	7.92 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/002 Course Curriculum.mp4	34.91 MB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/003 Course aim and knowledge requirements.en.srt	2.91 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/003 Course aim and knowledge requirements.mp4	15.51 MB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/004 Course Material.en.srt	2.26 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/004 Course Material.mp4	10.10 MB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/005 Jupyter notebooks.html	1.78 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/006 Presentations.html	1.15 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/007 Datasets.html	1.45 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/008 Set up your computer - required packages.html	1.61 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/01 Introduction/009 FAQ.html	3.76 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/02 Hyperparameter Tuning - Overview/001 Parameters and Hyperparameters.en.srt	13.72 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/02 Hyperparameter Tuning - Overview/001 Parameters and Hyperparameters.mp4	62.27 MB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/03 Performance metrics/001 Introduction.en.srt	1.49 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/03 Performance metrics/001 Introduction.mp4	5.81 MB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/03 Performance metrics/002 Classification Metrics (Optional).en.srt	9.64 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/05 Basic Search Algorithms/001 Basic Search Algorithms - Introduction.en.srt	6.59 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/05 Basic Search Algorithms/003 Grid Search.en.srt	4.49 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/05 Basic Search Algorithms/003 Grid Search.mp4	16.30 MB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/001 Sequential Search.en.srt	7.07 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/003 Bayesian Inference - Introduction.en.srt	9.27 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/003 Bayesian Inference - Introduction.mp4	43.42 MB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/004 Joint and Conditional Probabilities.en.srt	9.08 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/005 Bayes Rule.en.srt	14.00 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/006 Sequential Model-Based Optimization.en.srt	19.98 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/006 Sequential Model-Based Optimization.mp4	114.09 MB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/007 Gaussian Distribution.en.srt	8.72 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/011 Acquisition Functions.en.srt	15.94 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/012 Additional Reading Resources.html	2.23 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/014 Scikit-Optimize - Manual Search.en.srt	7.25 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/016 Scikit-Optimize - Alternative Kernel.en.srt	4.53 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/017 Scikit-Optimize - Neuronal Networks.en.srt	18.37 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/06 Bayesian Optimization/018 Scikit-Optimize - CNN - Search Analysis.en.srt	7.95 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/07 Other SMBO Algorithms/001 SMAC.en.srt	7.36 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/07 Other SMBO Algorithms/003 Tree-structured Parzen Estimators - TPE.en.srt	4.24 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/07 Other SMBO Algorithms/004 TPE Procedure.en.srt	9.40 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/07 Other SMBO Algorithms/005 TPE hyperparameters.en.srt	5.25 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/003 Hyperparameter Distributions.en.srt	5.18 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/004 Defining the hyperparameter space.en.srt	3.02 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/004 Defining the hyperparameter space.mp4	17.17 MB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/005 Defining the objective function.en.srt	2.51 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/007 Bayesian search with Gaussian processes.en.srt	6.77 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/009 Bayes search with GBMs.en.srt	3.68 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/010 Parallelizing a bayesian search.en.srt	3.31 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/012 Changing the kernel of a Gaussian Process.en.srt	4.53 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/012 Changing the kernel of a Gaussian Process.mp4	25.04 MB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/013 Optimizing xgboost.html	1.23 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/014 Optimizing parameters of a CNN.en.srt	18.37 kB
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[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/015 Analyzing the CNN search.en.srt	7.95 kB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/08 Scikit-Optimize/015 Analyzing the CNN search.mp4	37.08 MB
[TutsNode.com] - Hyperparameter Optimization for Machine Learning/09 Moving Forward/001 What's next_.html	1.56 kB

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Hyperparameter Optimization for Machine Learning