Machine Learning Projects

Machine Learning Projects - Beginner to Advanced

• Beginner Level
• Advanced Level

Technologies

There are several technologies used in machine learning, including:

1. Programming languages - Python, R, and Julia.
2. Data storage - SQL, NoSQL databases, and Hadoop.
3. ML Frameworks - TensorFlow, PyTorch, and scikit-learn.
4. Deep learning libraries - Keras, Theano, and Caffe.
5. Tools for Data Visualization & analysis - Matplotlib, ggplot, and Tableau.
6. Cloud platforms - AWS, GCP, Azure etc.

Types of Projects

Following are several types of projects in machine learning:

1. Supervised learning
   • Image classification
   • Regression analysis
   • Spam detection
2. Unsupervised learning
   • Clustering
   • Dimensionality reduction
   • Anomaly detection
3. Reinforcement learning
   • Game AI
   • Robotics
   • Recommendation systems
4. Transfer learning
   • Object detection
   • Sentiment analysis:
5. Generative models
   • GANs (Generative Adversarial Networks)
   • VAEs (Variational Autoencoders)
6. NLP (Natural Language Processing
   • Text classification
   • Language translation
   • Sentiment analysis

Beginner Level Projects

• Supervised learning

  1. Predicting housing prices
  2. Handwritten digit recognition
  3. Spam classification

• Unsupervised learning

  1. Customer segmentation
  2. Anomaly detection
  3. Image compression

• Reinforcement learning

  1. Gridworld navigation
  2. Game playing AI
  3. Stock trading agent

• Transfer learning

  • Object detection
  • Sentiment analysis

• Generative models

  • GANs (Generative Adversarial Networks)
    • Generative Inpainting Pytorch
    • Colorizing with GANs
    • GestureGAN
  • VAEs (Variational Autoencoders)

• NLP (Natural Language Processing

  • Text classification
  • Language translation

These projects can be implemented using popular machine learning libraries such as scikit-learn, TensorFlow, or PyTorch

Advanced Level Projects

• Supervised learning
  • Image Processing
    • Harris Corner Detection and Stitch Images
    • Iris Speed Sign
• Unsupervised learning
• Reinforcement learning
• Transfer learning
• Generative models
• NLP (Natural Language Processing

Contributions

• Guidelines