In response, it is suggested that a strong background in mathematics is often required for AI/ML engineers. They can get started with PyTorch, but should focus on linear algebra and optimization for deep learning, and statistics and probability for general data science.
Key takeaways:
- The author is a Software Engineer looking to transition into AI/ML engineering, having already started developing Co-pilots using Langchain, OpenAI, RAG.
- The author is seeking advice on what courses or books to read to build knowledge in AI/ML.
- A response suggests that a strong math background is usually required for AI/ML engineers, particularly in linear algebra and optimization for deep learning.
- For general data science, the responder recommends focusing on statistics and probability.