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  • ML Fundamentals
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Sentiment Analysis for Mental Health Using NLP & ML

Sentiment Analysis for Mental Health Using NLP & ML

Classify mental health statements using NLP and ML techniques. Includes preprocessing, TF-IDF, XGBoost, Random Over-Sampling, and real-world prediction applications.

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Skip Gram Model Python Implementation for Word Embeddings

Skip Gram Model Python Implementation for Word Embeddings

Everyone understands the fact that a language is made up of words. Moreover, combining them appropriately is essential in many intricate activities such as natural language processing (NLP) and machine learning.

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NLP Project for Beginners on Text Processing and Classification

NLP Project for Beginners on Text Processing and Classification

Get hands-on experience in NLP with a project focused on text processing and supervised classification.

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Topic modeling using K-means clustering to group customer reviews

Topic modeling using K-means clustering to group customer reviews

Analyze customer reviews with NLP, sentiment analysis, topic modeling, and K-Means clustering to uncover trends, and insights and improve business strategies.

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Credit Card Default Prediction Using Machine Learning Techniques

Credit Card Default Prediction Using Machine Learning Techniques

Preprocess data, engineer features, and apply models like Random Forest or XGBoost. Evaluate performance and use LIME/SHAP for interpretability.

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Build Regression Models in Python for House Price Prediction

Build Regression Models in Python for House Price Prediction

Build a model to predict house prices using Linear Regression. Understand data cleaning, feature selection, and model evaluation for accurate price forecasts.

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Build a Customer Churn Prediction Model using Decision Trees

Build a Customer Churn Prediction Model using Decision Trees

Predict customer churn with Decision Trees! Learn data cleaning, SMOTE, and model evaluation using Python. Compare Decision Tree and Logistic Regression models to find the best approach in this hands-on, beginner-friendly project.

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Build Regression (Linear, Ridge, Lasso) Models in NumPy Python

Build Regression (Linear, Ridge, Lasso) Models in NumPy Python

Build and evaluate regression models (Linear, Lasso, Ridge) to predict laptop prices with effective data preprocessing and performance metrics.

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Word2Vec and FastText Word Embedding with Gensim in Python

Word2Vec and FastText Word Embedding with Gensim in Python

Understand how CBOW, Skip-Gram, and FastText models capture word meanings, visualize embeddings, and evaluate model performance for various NLP tasks.

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BigMart Sales Prediction ML Project in Python

BigMart Sales Prediction ML Project in Python

Learn retail sales prediction with machine learning. This project builds regression models to analyze sales trends and drive data-driven decisions for retail success.

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Loan Eligibility Prediction using Gradient Boosting Classifier

Loan Eligibility Prediction using Gradient Boosting Classifier

Accurate loan eligibility prediction with machine learning, applying SMOTE, data processing, and Random Forest for fair and efficient credit decisions.

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Learn to Build a Polynomial Regression Model from Scratch

Learn to Build a Polynomial Regression Model from Scratch

Learn how to implement polynomial regression to capture complex patterns in data. Discover applications in finance, healthcare, and forecasting with detailed insights and methods.

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