Logistic Regression for Classification | Working with a real-world dataset from Kaggle
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In this lesson we will learn about using Logistic Regression for Classification. Logistic Regression is a commonly used technique for solving binary classification problems. You can experiment with the notebook used in the above video here 👉 https://jovian.ai/aakashns/python-skl...
🔗 Check out this playlist for the complete lecture series on Gradient Boosting Machines: • Machine Learning with Python: Zero to...
🎯 Topics Covered
• Downloading a real-world dataset from Kaggle
• Splitting a dataset into training, validation & test sets
• Imputing and scaling numeric features
• Encoding categorical columns as one-hot vectors
• Training a logistic regression model using Scikit-learn
• Evaluating a model using a validation set and test set
❓ Ask Questions here: https://jovian.ai/forum/t/lesson-2-lo...
classification/17915
⌚ Time Stamps:
00:00 Introduction
05:16 Problem Statement
25:43 Downloading a real-world dataset from Kaggle
35:35 Exploring data analysis and visualization
47:06 Splitting a dataset into training, validation & test sets
01:03:04 Filling/Imputing missing values in numeric columns
01:21:55 Scaling numeric features to a(0,1) range
01:28:10 Encoding categorical columns as one-hot vectors
01:39:02 Training a logistic regression model using Scikit-learn
01:53:41 Evaluating a model using a validation set and test set
02:19:38 Saving a model to disk and loading it back
02:36:28 Summary and Conclusion
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🔗 Visit the logistic regression lecture page here: https://jovian.ai/learn/machine-learn...
🎤 About the speaker
Aakash N S is the co-founder and CEO of Jovian - a community learning platform for data science & ML. Previously, Aakash has worked as a software engineer (APIs & Data Platforms) at Twitter in Ireland & San Francisco and graduated from the Indian Institute of Technology, Bombay. He’s also an avid blogger, open-source contributor, and online educator.
#GBM #MachineLearning #Python #Certification #Course #Jovian
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