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11 changes: 11 additions & 0 deletions How To Get Started With Generative AI.md
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Steps to get started:
1. Understanding basics: This is the first step. Knowing what generative AI is, what are it's applications and it's future scope.
2. Learning python: Python is the most important language in artificial intelligence and machine learning. Gradually knowing the basics then moving on to advanced python can help.
3. Python libraries: This is a bit advanced version of python. Understand libraries like TensorFlow, PyTorch, and Keras is esential to understand machine learning.
4. Understanding machine learning basics: The next step is to understand what is superwised learning, unsuperwised learning, and reinforcement learning.
5. Deep learning: Artificial intelligence often relies on neural networks. The next step is to understand deep learning fundamentals like neural networks, backpropagation, and gradient descent.
6. Exploring generative AI models: Explore different generative models. The most popular ones include Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Recurrent Neural Networks (RNNs).
7. Building small models: It is a good idea to start building small models in the beginning like a model to generate text or images.
8. Online courses: There are various online courses available on platforms like coursera and edx.
9. Specialisations: After exploring all domains of generative AI, it is good to specialise in 1 domain of it like text generation, or specifically image generation, etc.
10. Tools and Frameworks: Familiarize yourself with the tools and frameworks used in generative AI, like Jupyter notebooks, Google Colab, and cloud computing platforms for training large models.