Day 18-Fake news detection – Naïve Baye’s
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Day 1- Python Programming – Fundamentals
Day 2- Python – Tools | Syntaxes & Data Structures
Day 3- Machine Learning Concepts
Day 4- Pandas Library – Introduction
Day 5- Pandas – Data Structures
Day 6- Numpy library – Array Operations | Mathematical Functions
Day 7- Numpy – Sort , Search and Counting Functions | Byte Swapping
Day 8- Matplotlib , Histogram Using Matplotlib | I/O With Numpy
Day 9- Matplotlib Library – Introduction , Pyplot API | Types Of Plots
Day 10- Seaborn Library
Day 11- SKLearn Library
Day 12- Google Colab Notebook
Day 13- Data Preparation & Visualisation
Day 14- Data Normalization Techniques
Day 15- Introduction to supervised learning algorithms.
Day 16-Liver Disease Prediction – Logistic Regression
Day 17-Flower Species Identification – SVM Algorithm.
Day 18-Fake news detection – Naïve Baye’s
Day 19-Android malware – Decision tree Algorithm.
Day 20- Credit_card Fraud detection – Random Forest Algorithm
Day 21- Employee Salary Prediction – Linear Regression Algorithm
Day 22- Advertisement and Sales Prediction – Multiple Linear Regression Algorithm.
Day 23- Agriculture Price Prediction – Random Forest Regression.
Day 24- Flower Species Data Visualization – PCA
Day 25- Market Basket Analysis – APRIARI
Day 26- Hate Speech Detection – NLTK
Day 27 – Loan Prediction Problem – XGBoost
Day 28-Movie Review Classification- RNN
Day 29-Digits Classification – CNN
Day 30-AI – Cart Pole – Reinforcement Learning
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