1. Deep Learning Specialization by Ng @Coursera
2. Deep Learning for Coders with fastai and PyTorch by Jeremy Howard
3. Learn PyTorch really well. Either use d2l.ai or the PyTorch book from Manning.
START MAKING PROJECTS HERE
>> Jump the hype train of LLM?
1. Natural Language Processing specialization @Coursera
2. Multilingual NLP from CMU
3. Learn using HuggingFace with either their book or course.
Your path from here will be visible to you.
>> Jump the hype train of multimodal AI like Stable Diffusion, Dall-E, etc.?
1. Diffusers course from HuggingFace.
2. Plenty of resources out there in the forms of blogs, oss projects, etc.
>> Want Edge AI, Federated Learning, or Deep RL?
There are great resources like:
1. Deep RL course from Hugging Face
2. Deep Reinforcement Learning in Action by Zai, Brown
3. Federated Learning course by Openmined
4. Edge AI course from Harvard at edX
5. Edge AI course from Edge Impulse
There are also cool stuff happening in the Math+DL and Science+DL spaces. There are nice resources for those, too.
A bit of advice, don't take too many courses and focus on building stuff, and take courses when you think that a gap exists in your knowledge.
Deep Learning from NYU is taught by Yann LeCun and Alfredo Canziani, and it is pure gem.
You will feel the need of learning math when you advance.
Mathematics for ML from Imperial College London is great.
So is Strang's Linear Algebra.
1. Deep Learning Specialization by Ng @Coursera
2. Deep Learning for Coders with fastai and PyTorch by Jeremy Howard
3. Learn PyTorch really well. Either use d2l.ai or the PyTorch book from Manning.
Now it depends where you want to go.>> Jump the hype train of LLM?
1. Natural Language Processing specialization @Coursera
2. Multilingual NLP from CMU
3. Learn using HuggingFace with either their book or course.
Your path from here will be visible to you.
>> Jump the hype train of multimodal AI like Stable Diffusion, Dall-E, etc.?
1. Diffusers course from HuggingFace.
2. Plenty of resources out there in the forms of blogs, oss projects, etc.
>> Want Edge AI, Federated Learning, or Deep RL?
There are great resources like:
1. Deep RL course from Hugging Face
2. Deep Reinforcement Learning in Action by Zai, Brown
3. Federated Learning course by Openmined
4. Edge AI course from Harvard at edX
5. Edge AI course from Edge Impulse
There are also cool stuff happening in the Math+DL and Science+DL spaces. There are nice resources for those, too.
A bit of advice, don't take too many courses and focus on building stuff, and take courses when you think that a gap exists in your knowledge.
Deep Learning from NYU is taught by Yann LeCun and Alfredo Canziani, and it is pure gem.
You will feel the need of learning math when you advance.
Mathematics for ML from Imperial College London is great.
So is Strang's Linear Algebra.