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Machine Learning Tutorial Python | Machine Learning For Beginners

5.0 (3)
25 learners

What you'll learn

This course includes

  • 12 hours of video
  • Certificate of completion
  • Access on mobile and TV

Course content

1 modules • 42 lessons • 12 hours of video

Machine Learning Tutorial Python | Machine Learning For Beginners

42 lessons • 12 hours
  • Machine Learning Tutorial Python -1: What is Machine Learning?06:51
  • Machine Learning Tutorial Python - 2: Linear Regression Single Variable15:14
  • Machine Learning Tutorial Python - 3: Linear Regression Multiple Variables14:08
  • Machine Learning Tutorial Python - 4: Gradient Descent and Cost Function28:26
  • Machine Learning Tutorial Python - 5: Save Model Using Joblib And Pickle08:21
  • Machine Learning Tutorial Python - 6: Dummy Variables & One Hot Encoding21:35
  • Machine Learning Tutorial Python - 7: Training and Testing Data06:34
  • Machine Learning Tutorial Python - 8: Logistic Regression (Binary Classification)19:19
  • Machine Learning Tutorial Python - 8 Logistic Regression (Multiclass Classification)15:43
  • Machine Learning Tutorial Python - 9 Decision Tree14:46
  • Machine Learning Tutorial Python - 10 Support Vector Machine (SVM)23:22
  • Machine Learning Tutorial Python - 11 Random Forest12:48
  • Machine Learning Tutorial Python 12 - K Fold Cross Validation25:20
  • Machine Learning Tutorial Python - 13: K Means Clustering Algorithm25:15
  • Machine Learning Tutorial Python - 14: Naive Bayes Classifier Algorithm Part 113:38
  • Machine Learning Tutorial Python - 15: Naive Bayes Classifier Algorithm Part 211:28
  • Machine Learning Tutorial Python - 16: Hyper parameter Tuning (GridSearchCV)16:30
  • Machine Learning Tutorial Python - 17: L1 and L2 Regularization | Lasso, Ridge Regression19:21
  • Machine Learning & Data Science Project - 1 : Introduction (Real Estate Price Prediction Project)02:12
  • Machine Learning & Data Science Project - 2 : Data Cleaning (Real Estate Price Prediction Project)15:21
  • Machine Learning & Data Science Project - 3 : Feature Engineering (Real Estate Price Prediction)08:26
  • Machine Learning & Data Science Project - 4 : Outlier Removal (Real Estate Price Prediction Project)19:31
  • Machine Learning & Data Science Project - 5 : Model Building (Real Estate Price Prediction Project)19:12
  • Machine Learning & Data Science Project - 6 : Python Flask Server (Real Estate Price Prediction)21:13
  • Machine Learning & Data Science Project - 7 : Website or UI (Real Estate Price Prediction Project)13:21
  • Deploy machine learning model to production AWS (Amazon EC2 instance)28:39
  • Data Science & Machine Learning Project - Part 1 Introduction | Image Classification04:42
  • Data Science & Machine Learning Project - Part 2 Data Collection | Image Classification05:37
  • Data Science & Machine Learning Project - Part 3 Data Cleaning | Image Classification40:45
  • Data Science & Machine Learning Project - Part 4 Feature Engineering | Image Classification18:23
  • Data Science & Machine Learning Project - Part 5 Training a Model | Image Classification20:01
  • Data Science & Machine Learning Project - Part 6 Flask Server | Image Classification36:16
  • Data Science & Machine Learning Project - Part 7 Build Website | Image Classification38:14
  • Data Science & Machine Learning Project - Part 8 Deployment & Exercise | Image Classification05:17
  • Machine Learning Tutorial Python - 18: K nearest neighbors classification with python code15:42
  • Machine Learning Tutorial Python - 19: Principal Component Analysis (PCA) with Python Code24:09
  • Machine Learning Tutorial Python - 20: Bias vs Variance In Machine Learning10:50
  • Machine Learning Tutorial Python - 21: Ensemble Learning - Bagging23:37
  • What is feature engineering | Feature Engineering Tutorial Python # 105:12
  • Outlier detection and removal using percentile | Feature engineering tutorial python # 217:18
  • Outlier detection and removal: z score, standard deviation | Feature engineering tutorial python # 320:05
  • Outlier detection and removal using IQR | Feature engineering tutorial python # 408:02

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