Linking pages
- How to deliver on Machine Learning projects | by Emmanuel Ameisen | Insight https://blog.insightdatascience.com/how-to-deliver-on-machine-learning-projects-c8d82ce642b0 39 comments
- An Introduction to Recurrent Neural Networks for Beginners - victorzhou.com https://victorzhou.com/blog/intro-to-rnns/ 25 comments
- The Best RNN for Image Classification: RNN, LSTM, or GRU? https://pythonalgos.com/the-best-rnn-for-image-classification-rnn-lstm-or-gru/ 3 comments
- An Intuitive Guide to Deep Network Architectures | by Joyce Xu | Towards Data Science https://medium.com/towards-data-science/an-intuitive-guide-to-deep-network-architectures-65fdc477db41 1 comment
- Backpropaganda: anti-rational neuro-mythology | Better without AI https://betterwithout.ai/backpropaganda 1 comment
- An overview of activation functions used in neural networks https://adl1995.github.io/an-overview-of-activation-functions-used-in-neural-networks.html 0 comments
- ML From Scratch, Part 3: Backpropagation - OranLooney.com http://www.oranlooney.com/post/ml-from-scratch-part-3-backpropagation/ 0 comments
- A Gentle Introduction to the Rectified Linear Unit (ReLU) - MachineLearningMastery.com https://machinelearningmastery.com/rectified-linear-activation-function-for-deep-learning-neural-networks/ 0 comments
- Modern Theory of Deep Learning: Why Does It Work so Well | by Dmytrii S. | ML Review https://medium.com/mlreview/modern-theory-of-deep-learning-why-does-it-works-so-well-9ee1f7fb2808 0 comments
- Can increasing depth serve to accelerate optimization? – Off the convex path http://www.offconvex.org/2018/03/02/acceleration-overparameterization/ 0 comments
- Minimum elucidating examples https://bastian.rieck.me/blog/posts/2020/elucidating_examples/ 0 comments
- Recurrent Neural Networks Explained with a Real Life Example and Python Code | by Carolina Bento | Towards Data Science https://towardsdatascience.com/recurrent-neural-networks-explained-with-a-real-life-example-and-python-code-e8403a45f5de 0 comments
- How to train your Deep Neural Network – Rishabh Shukla http://rishy.github.io/ml/2017/01/05/how-to-train-your-dnn/ 0 comments
- Back-propagation, an introduction – Off the convex path http://www.offconvex.org/2016/12/20/backprop/ 0 comments
- Can increasing depth serve to accelerate optimization? – Off the convex path http://offconvex.github.io/2018/03/02/acceleration-overparameterization/ 0 comments
- YinYangFit https://skosch.github.io/YinYangFit/ 0 comments
- Making Sense of eBay’s Image Similarity Search Algorithm | by Luke Kerbs | Oct, 2022 | Medium https://medium.com/@lukekerbs/making-sense-of-ebays-image-similarity-search-algorithm-d9f1b3a6668c 0 comments
- Activation Functions : Sigmoid, tanh, ReLU, Leaky ReLU, PReLU, ELU, Threshold ReLU and Softmax basics for Neural Networks and Deep Learning | by Himanshu S | Medium https://medium.com/@himanshuxd/activation-functions-sigmoid-relu-leaky-relu-and-softmax-basics-for-neural-networks-and-deep-8d9c70eed91e 0 comments
- Deep Learning for NLP: An Overview of Recent Trends | by elvis | DAIR.AI | Medium https://medium.com/dair-ai/deep-learning-for-nlp-an-overview-of-recent-trends-d0d8f40a776d 0 comments
- Fundamentals of Retrieval Augmentation Generation (RAG) https://manel.dev/fundamental-rag 0 comments
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