Machine Learning with Python Part 2 - Model Training and Evaluation

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Machine Learning with Python Part 2 - Model Training and Evaluation

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Welcome to Part 2 of our Machine Learning tutorial series! In this video, we take a deep dive into model training and evaluation using Python. Building upon the concepts covered in Part 1, we guide you through the process of developing and refining predictive models.

Join us as we explore popular Machine Learning algorithms, including decision trees, support vector machines, and ensemble methods. Learn how to train models, optimize hyperparameters, and evaluate their performance using various metrics. We provide practical examples using Python and libraries like scikit-learn.

By the end of this tutorial, you'll have a comprehensive understanding of model training, selection, and evaluation in Machine Learning. Subscribe to our channel to stay updated with our latest tutorials and enhance your skills in Python-based Machine Learning!

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00:00 - Overview
00:56 - Role of Algorithm ?
02:40 - Selecting Algorithm for Machine Learning
11:26 - Training The Model for Machine Learning
18:37 - Splitting Data and Training the Model
05:53 - Supervised Machine Learning Vs. unsupervised Machine Learning
12:35 - Getting started with Python and Jupyter Notebook
33:02 - Testing The Model's Accuracy
55:45 - Summary

Tags: #MachineLearning #PythonTutorial #ModelTraining #ModelEvaluation #DecisionTrees #SupportVectorMachines #EnsembleMethods #HyperparameterOptimization #ScikitLearn #PredictiveModels#ModelTrainingTechniques #ModelSelection #ModelEvaluationMethods #DecisionTreeAlgorithms #SupportVectorMachine #EnsembleLearning #HyperparameterTuning #ModelPerformanceMetrics #ScikitLearnTutorial #MachineLearningModels #ModelOptimization #ModelComparison #ModelMetrics #ModelValidation #Overfitting #Underfitting

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I remember learning something like this a few years ago but never quite understood and now it finally clicked. Thank You much!

ShahZ

Courses like this are an important component towards the democratization of AI. Hopefully courses like this + open-sourced models will always be available to us. Thank you for being so generous with your knowledge. Nicely done as always.

wadejohnson

I wish I have more of your content. Good job.

dogbatsealfredmawuli

is there upcoming part 3, 4, 5, ..., n+1 ? because im loving your videos and started to understanding the workflow of ML

zulkifliarshad

You may probably start with some mathematical intuitions of different models...then writing code (like scikit-learn)

shakilkhan

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