Learn AI and ML: Create your own projects in 10 lessons!
Want to get started in the field of artificial intelligence and machine learning, but staggered by the amount of resources and documentation that you can choose from?
In this Bughouse Course, I'll guide you through everything you need while also focusing on production and practicality. I'll go through both the fundamentals and advanced concepts, enabling you to create your own AI projects as soon as possible.
For now, don't worry too much about the fancy titles and descriptions. By the time you finish Lesson 10, you'll already be making and learning with your own models!
Share your progress with me on Twitter! Then, for exclusive tips to launch AI/ML projects even more quickly!
Lesson 1: Foundations of Machine Learning
Start with the basics. Concepts, Math, and Python.
Lesson 2: PyTorch Basics and Neural Networks
Let's train a simple neural network. Tensor operations, gradient descent, and backpropagation.
Lesson 3: Supervised Learning: From Linear Models to Deep Neural Networks
Explore the core of machine learning. Regressions, multilayer perceptrons, and loss functions and optimization.
Lesson 4: Computer Vision with Convolutional Neural Networks (CNNs)
Dive into image processing. Image classification, transfer learning, and object detection.
Lesson 5: Natural Language Processing (NLP) and Sequence Models
The power of language. Text preprocessing, recurrent neural networks, and sentiment analysis.
Lesson 6: Unsupervised Learning and Dimensionality Reduction
Discover patterns in unlabeled data. Clustering (K-means), principal component analysis, and autoencoders.
Lesson 7: Generative Models: VAEs and GANs
Create new data. Variational autoencoders, generative adversarial networks, and basic image gen.
Lesson 8: Advanced Deep Learning: Attention and Transformers
Let's look deeper. Attention mechanisms, transformer architecture, and BERT.
Lesson 9: Model Deployment and Ethical AI
Bring your models to production. Model deployment, interpretability, bias, and responsibility in AI.
Lesson 10: Diffusion Models: From Theory to Practice
Build cutting-edge generative models. Implementing diffusion models and scaling up.
Extra Resources
Additional tips and materials to support your learning. I personally use these!