Topics

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 Employee using POLYNOMIAL REGRESSION

Day-14: Stock price prediction using SUPPORT VECTOR REGRESSION

Day-15: Height Prediction from the Age using DECISION TREE REGRESSION

Day-16: Car price prediction using RANDOM FOREST

Day-17: Evaluating Regression model performance using R-SQUARED INTUITION & ADJUSTED R-SQUARED INTUITION

Day-18: Regression Model Selection for Engine Energy prediction.

UNSUPERVISED LEARNING - CLUSTERING

Day-19: Identifying the Pattern of the Customer spent using K-MEANS CLUSTERING

Day-20: Customer Spending analysis using HIERARCHICAL CLUSTERING

Day-21: Leaf types data visualization using PRINCIPLE COMPONENTANALYSIS

Day-22: Finding Similar Movie based on ranking using SINGULAR VALUEDECOMPOSITION

UNSUPERVISED LEARNING - ASSOCIATION

Day-23: Market Basket Analysis using APIRIORI

Day-24: Market Basket Optimization/Analysis using ECLAT

REINFORCEMENT LEARNING

Day-25: Web Ads. Click through Rate optimization using UPPER BOUNDCONFIDENCE

Natural Language Processing

Day-26: Sentimental Analysis using Natural Language Processing

Day-27: Breast cancer Tumor prediction using XGBOOST

DEEP LEARNING

Day-28: Pima-Indians Diabetes Classification

Day-29: Covid-19 Detection using CNN

Day-30: A.I Snake Game using REINFORCEMENT LEARNING