Udemy Machine Learning AI Python

03 - Data Preprocessing in Python/003 Machine Learning Toolkit Importing NumPy, Matplotlib, and Pandas Libraries.mp4

03 - Data Preprocessing in Python/004 Step 1 - Machine Learning Basics Importing Datasets Using Pandas read_csv().mp4

03 - Data Preprocessing in Python/009 Step 1 - Using Scikit-Learn to Replace Missing Values in Machine Learning.mp4

03 - Data Preprocessing in Python/019 Coding Exercise 4 Dataset Splitting and Feature Scaling.html

03 - Data Preprocessing in Python/015 Coding Exercise 3 Encoding Categorical Data for Machine Learning.html

03 - Data Preprocessing in Python/024 Coding exercise 5 Feature scaling for Machine Learning.html

03 - Data Preprocessing in Python/008 Coding Exercise 1 Importing and Preprocessing a Dataset for Machine Learning.html

03 - Data Preprocessing in Python/010 Step 2 - Imputing Missing Data in Python SimpleImputer and Numerical Columns.mp4

03 - Data Preprocessing in Python/022 Step 3 - Implementing Feature Scaling Fit and Transform Methods Explained.mp4

03 - Data Preprocessing in Python/005 Step 2 - Using Pandas iloc for Feature Selection in ML Data Preprocessing.mp4

03 - Data Preprocessing in Python/006 Step 3 - Preprocessing Data Building X and Y Vectors for ML Model Training.mp4

03 - Data Preprocessing in Python/011 Coding Exercise 2 Handling Missing Data in a Dataset for Machine Learning.html

03 - Data Preprocessing in Python/023 Step 4 - Applying the Same Scaler to Training and Test Sets in Python.mp4

03 - Data Preprocessing in Python/002 Step 2 - Data Preprocessing Techniques From Raw Data to ML-Ready Datasets.mp4

03 - Data Preprocessing in Python/017 Step 2 - Preparing Data Creating Training and Test Sets in Python for ML Models.mp4

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