In this python machine learning tutorial for beginners we will look into,
1) how to hyper tune machine learning model paramers
2) choose best model for given machine learning problem
We will start by comparing traditional train_test_split approach with k fold cross validation. Then we will see how GridSearchCV helps run K Fold cross validation with its convenient api. GridSearchCV helps find best parameters that gives maximum performance. RandomizedSearchCV is another class in sklearn library that does same thing as GridSearchCV
but without running exhaustive search, this helps with computation time and resources. We will also see how to find best model among all the classification algorithm using GridSearchCV. In the end we have interesting exercise for you to solve.

#MachineLearning #PythonMachineLearning #MachineLearningTutorial #Python #PythonTutorial #PythonTraining #MachineLearningCource #HyperParameter #GridSearchCV #sklearntutorials #scikitlearntutorials

Exercise: [ Ссылка ]
Code in this tutorial: [ Ссылка ]

Do you want to learn technology from me? Check [ Ссылка ] for my affordable video courses.

Exercise solution: [ Ссылка ]

Topics that are covered in this Video:
00:00 Introduction
00:45 train_test_split to find model performance
01:37 K fold cross validation
04:44 GridSearchCV for hyperparameter tuning
10:18 RandomizedSearchCV
12:35 Choosing best model
15:25 Exercise

Next Video:
Deep Learning Tutorial Python, Tensorflow And Keras: Introduction and Installation: [ Ссылка ]

Populor Playlist:
Data Science Full Course: [ Ссылка ]

Data Science Project: [ Ссылка ]

Machine learning tutorials: [ Ссылка ]

Pandas: [ Ссылка ]

matplotlib: [ Ссылка ]

Python: [ Ссылка ]

Jupyter Notebook: [ Ссылка ]

Tools and Libraries:
Scikit learn tutorials
Sklearn tutorials
Machine learning with scikit learn tutorials
Machine learning with sklearn tutorials

🌎 My Website For Video Courses: [ Ссылка ]

Need help building software or data analytics and AI solutions? My company [ Ссылка ] can help. Click on the Contact button on that website.

#️⃣ Social Media #️⃣
🔗 Discord: [ Ссылка ]
📸 Dhaval's Personal Instagram: [ Ссылка ]
📸 Codebasics Instagram: [ Ссылка ]
🔊 Facebook: [ Ссылка ]
📱 Twitter: [ Ссылка ]
📝 Linkedin (Personal): [ Ссылка ]
📝 Linkedin (Codebasics): [ Ссылка ]
🔗 Patreon: [ Ссылка ]

свернуть