learning-dnns

this is repository containing selected books , courses, labs, projects, papers and other materials related with deep neural networks and machine learning in general.

books:

• deeplearningbook.org

The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free.

courses:

• dintrotodeeplearning.com/. Videos, slides, labs avilable under archived version tag.

MIT's official introductory course on deep learning methods with applications to machine translation, image recognition, game playing, and more. Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow.

• Coursea, Deep Learning Specialization. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.

cheatsheet:

• ml-cheatsheet backpropagation

Brief visual explanations of machine learning concepts with diagrams, code examples and links to resources for learning more.

• Derivative of Cross Entropy Loss with Softmax explained

• cnn explained

training models hints:

• Better Deep Learning, Train Faster, Reduce Overfitting, and Make Better Predictions

blogs:

• An overview of gradient descent optimization algorithms
• intro to style transfer

papers:

• papers with code collection
• Visualizing the Loss Landscape of Neural Nets

CNNs:

• skip architecture intro
• Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue

Youtube:

• Batch normalization explained
• Encoder-decoder demo

frameworks:

• opencv + halide/openVino
• dlib

interesting concepts/ides:

• denseNet, extended ResNet block
• Capsue Network, pose invariance
• Towards Deep Symbolic Reinforcement Learning
• Learnable Histograms
• NeuroSat

code collections:

• modelzoo Discover open source deep learning code and pretrained models.