Some of the best resources to learn deep learning in 2020 include online courses, textbooks, and research papers. Online platforms like Coursera and edX offer popular courses such as the “Deep Learning Specialization” by Andrew Ng and “CS231n: Convolutional Neural Networks for Visual Recognition” from Stanford University. These courses provide hands-on experience with deep learning concepts and practical applications. Textbooks like “Deep Learning” by Ian Goodfellow and Yoshua Bengio, and “Deep Learning with Python” by François Chollet are excellent resources for understanding both the theoretical and practical aspects of deep learning. These books cover topics like neural networks, CNNs, RNNs, and advanced techniques such as reinforcement learning and GANs. Research papers and arXiv.org provide cutting-edge developments in the field. Following influential conferences such as NeurIPS, CVPR, and ICML also offers insight into the latest advancements in deep learning research. Participating in online communities like Reddit, StackOverflow, or Kaggle can help stay updated and solve practical problems in deep learning.
What are the best resources to learn about deep learning?
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- Natural Language Processing (NLP) Advanced Guide
- Accelerated Vector Search
- The Definitive Guide to Building RAG Apps with LangChain
- Vector Database 101: Everything You Need to Know
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