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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
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
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
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
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 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
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 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
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
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
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 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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