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Internship on Machine Learning - தமிழ்
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Day-1
Introduction to Data Science, Data Analytics, A.I, M.L, D.L, NLP | RoadMap (51:59)
Day 02
Day-2: Introduction to Python | How to write code in Google Colab, Jupyter Notebook, Pycharm & IDLE (36:45)
Day 03
Advertisement Sale prediction from an existing customer using LOGISTIC REGRESSION (74:25)
Day 04
Salary Estimation using K-NEAREST NEIGHBOR (58:58)
Day 05
Character Recognition using SUPPORT VECTOR MACHINE (44:09)
Day 06
Titanic Survival Prediction using NAIVE BAYES (38:15)
Day 07
Leaf Detection using DECISION TREE (37:49)
Day 08
Handwritten digit recognition using RANDOM FOREST (27:55)
Day 09
Evaluating Classification model Performance (41:55)
Day 10
Classification Model Selection for Breast Cancer classification (28:46)
Day 11
House Price Prediction using LINEAR REGRESSION Single Variable (30:55)
Day 12
Exam Mark Prediction using LINEAR REGRESSION Multiple Variable (15:28)
Day 13
Predicting the Previous salary of the New Employee using POLYNOMIAL REGRESSION (28:10)
Day 14
Stock price prediction using SUPPORT VECTOR REGRESSION (22:33)
Day 15
Height Prediction from the Age using DECISION TREE REGRESSION (24:19)
Day 16
Car price prediction using RANDOM FOREST (23:20)
Day 17
Evaluating Regression model performance (15:36)
Day 18
Regression Model Selection for Engine Energy prediction (19:05)
Day 19
Identifying the Pattern of the Customer spent using K-MEANS CLUSTERING (30:01)
Day 20
Customer Spending analysis using HIERARCHICAL CLUSTERING (21:45)
Day 21
Leaf types data visualization using PRINCIPLE COMPONENT ANALYSIS (20:49)
Day 22
Finding Similar Movie based on ranking using SINGULAR VALUE DECOMPOSITION (31:11)
Day 23 and Day 24
Market Basket Analysis using APIRIORI, Market Basket Optimization/Analysis using ECLAT (26:51)
Day 25
Web Ads. Click through Rate optimization using UPPER BOUND CONFIDENCE (32:54)
Day 26
Sentimental Analysis using Natural Language Processing (41:02)
Day 27
Breast cancer Tumor prediction using XGBOOST (27:07)
Day 28
Pima-Indians Diabetes Classification (33:51)
Day 29
Covid-19 Detection using CNN (33:15)
Day 30
A.I Snake Game using REINFORCEMENT LEARNING (25:57)
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Identifying the Pattern of the Customer spent using K-MEANS CLUSTERING
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