AI Mentor: Your Path to AI Mastery

A step-by-step journey from FastAPI to NLP, following Kaizen (continuous improvement) and KISS (keep it simple) principles. Think like an AI entrepreneur, not just a coder.

Kaizen Principle

Small, continuous improvements lead to mastery. Focus on consistent progress, not perfection.

KISS Principle

Keep It Simple, Stupid. Avoid complexity. Master fundamentals before advanced concepts.

1

FastAPI Fundamentals

Build robust APIs to serve your AI models

Key Concepts

  • API design and REST principles
  • Request/response models
  • Data validation with Pydantic
  • Authentication and security
  • Documentation with Swagger UI

Hands-on Exercises

  • Create a simple "Hello World" API
  • Build a CRUD API for a simple database
  • Add authentication to your API
  • Create API documentation

Practical Project

Build a Book Recommendation API that suggests books based on user preferences.

Best Resources

  • FastAPI Official Documentation
  • "FastAPI" by William S. Vincent
  • TestDriven.io FastAPI courses
AI Entrepreneur Thinking: How can your API create value? Think about monetization strategies like API-as-a-service or integration with existing platforms.
2

Machine Learning

Teach computers to learn from data

Key Concepts

  • Supervised vs. unsupervised learning
  • Regression and classification
  • Feature engineering
  • Model evaluation metrics
  • Bias-variance tradeoff

Hands-on Exercises

  • Implement linear regression from scratch
  • Build a spam classifier
  • Create a recommendation system
  • Optimize model hyperparameters

Practical Project

Develop a House Price Prediction model using real estate data.

Best Resources

  • "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow"
  • Andrew Ng's Machine Learning course
  • Kaggle Learn courses
AI Entrepreneur Thinking: Identify business problems that ML can solve. Consider creating a specialized ML service for a specific industry like healthcare or finance.
3

Deep Learning

Neural networks for complex pattern recognition

Key Concepts

  • Neural network architecture
  • Activation functions
  • Backpropagation and gradient descent
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)

Hands-on Exercises

  • Build a neural network from scratch with NumPy
  • Create an image classifier with CNNs
  • Implement text generation with RNNs
  • Use transfer learning for custom tasks

Practical Project

Build an Image Recognition System that identifies objects in real-time.

Best Resources

  • "Deep Learning" by Ian Goodfellow
  • Fast.ai Practical Deep Learning course
  • TensorFlow and PyTorch documentation
AI Entrepreneur Thinking: Deep learning models require significant computational resources. Consider cloud-based solutions and explore B2B applications where accuracy justifies higher costs.
4

Natural Language Processing

Understand and generate human language

Key Concepts

  • Tokenization and text preprocessing
  • Word embeddings (Word2Vec, GloVe)
  • Transformers and attention mechanisms
  • Named Entity Recognition (NER)
  • Sentiment analysis

Hands-on Exercises

  • Build a sentiment analysis tool
  • Create a text summarizer
  • Implement a chatbot
  • Fine-tune a transformer model

Practical Project

Develop a Smart Content Analyzer that extracts key insights from documents.

Best Resources

  • "Speech and Language Processing" by Jurafsky & Martin
  • Hugging Face Transformers course
  • Stanford CS224N: NLP with Deep Learning
AI Entrepreneur Thinking: NLP has massive applications in customer service, content creation, and data analysis. Consider creating specialized tools for specific industries or integrating with existing platforms.

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