2206.13446.pdf
3 MB
Book: 📚Exercises in Machine Learning
Authors: Michael U. Gutmann
year: 2024
pages: 211
Authors: Michael U. Gutmann
year: 2024
pages: 211
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Here are the top 5 machine learning projects that are suitable for freshers to work on:
1. Predicting House Prices: Build a machine learning model that predicts house prices based on features such as location, size, number of bedrooms, etc. This project will help you understand regression techniques and feature engineering.
2. Image Classification: Create a model that can classify images into different categories such as cats vs. dogs, fruits, or handwritten digits. This project will introduce you to convolutional neural networks (CNNs) and image processing.
3. Sentiment Analysis: Develop a sentiment analysis model that can classify text data as positive, negative, or neutral. This project will help you learn natural language processing techniques and text classification algorithms.
4. Credit Card Fraud Detection: Build a model that can detect fraudulent credit card transactions based on transaction data. This project will help you understand anomaly detection techniques and imbalanced classification problems.
5. Recommendation System: Create a recommendation system that suggests products or movies to users based on their preferences and behavior. This project will introduce you to collaborative filtering and recommendation algorithms.
Credits: https://t.me/free4unow_backup
All the best 👍👍
1. Predicting House Prices: Build a machine learning model that predicts house prices based on features such as location, size, number of bedrooms, etc. This project will help you understand regression techniques and feature engineering.
2. Image Classification: Create a model that can classify images into different categories such as cats vs. dogs, fruits, or handwritten digits. This project will introduce you to convolutional neural networks (CNNs) and image processing.
3. Sentiment Analysis: Develop a sentiment analysis model that can classify text data as positive, negative, or neutral. This project will help you learn natural language processing techniques and text classification algorithms.
4. Credit Card Fraud Detection: Build a model that can detect fraudulent credit card transactions based on transaction data. This project will help you understand anomaly detection techniques and imbalanced classification problems.
5. Recommendation System: Create a recommendation system that suggests products or movies to users based on their preferences and behavior. This project will introduce you to collaborative filtering and recommendation algorithms.
Credits: https://t.me/free4unow_backup
All the best 👍👍
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