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UTAustinAIMLProjects

This is a collection of my projects completed for my certification in AI/ML from UT-Austin.

Fundamentals:

Course 1: Fundamentals of AI
Project 1: CardioGoodFitness
Topics Covered:
    Python Fundamentals 
    Python for Data Science 
    Data Visualization and EDA

Machine Learning Courses:

Course 2: Regression
Project 2: Cars4U
Topics Covered:
    Linear Regression
    Data Preprocessing
    
Course 3: Classification
Project 3: Bancassurance
Topics Covered:
    Logistic Regression
    Decision Tree Classifiers
    GridSearch Algorithms

Course 4: Ensemble Techniques
Project 4: Travel Package Purchase Protection
Topics Covered:
    Bagging
    Random Forest
    Boosting
    
Course 5: Feature Selection, Model Selection, and Tuning
Project 5: Credit Card Users Churn Prediction
Topics Covered:
    Regularization
    Feature Engineering
    Handling Imbalanced Data
    
Course 6: Unsupervised Learning
Project 6: AllLife_Bank_Customer_Segmentation
Topics Covered:
    K means Clustering
    Hierarchical Clustering
    PCA

Deep Learning Courses:

Course 7: Introduction to Neural Networks
Project 7: Bank_Churn_Prediction
Topics Covered:
    Pre-work for Deep Learning
    Intro to ANN, Tensorflow, and Keras
    Building Blocks of ANN

Course 8: Introduction to Computer Vision
Project 8: COVID-19 Image Classification
Topics Covered:
    Pre-Work for CNN
    Intro to CNN - Working with Images
    Transfer Learning
    
Course 9: Introduction to Natural Language Processing
Project 9: Twitter US Airline Sentiment
Topics Covered:
    Intro to NLP- Working with Text Data
    Sentiment Analysis

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