Topics to be discussed in this 30 Days webinar Day-1: Overview A.I | Machine Learning Day-2: Introduction to Python | How to write code in Google Colab, Jupyter Notebook, Pycharm & IDLE SUPERVISED LEARNING - CLASSIFICATION & REGRESSION Day-3: Advertisement Sale prediction from an existing customer using LOGISTIC REGRESSION Day-4: Salary Estimation using K-NEAREST NEIGHBOR Day-5: Character Recognition using SUPPORT VECTOR MACHINE Day-6: Titanic Survival Prediction using NAIVE BAYES Day-7: Leaf Detection using DECISION TREE Day-8: Handwritten digit recognition using RANDOM FOREST Day-9: Evaluating Classification model Performance using CONFUSION MATRIX, CAP CURVE ANALYSIS & ACCURACY PARADOX Day-10: Classification Model Selection for Breast Cancer classification Day-11: House Price Prediction using LINEAR REGRESSION Single Variable Day-12: Exam Mark Prediction using LINEAR REGRESSION Multiple Variable Day-13: Predicting the Previous salary of the New Employe...
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