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Deep Learning Roadmap

Below you’ll find the Deep Learning Engineers roadmap - a step-by-step guide on how to become a Deep Learning Engineer. This not a beginners track! Make sure that you have completed the other roadmaps before jumping on this track! 

Deep Learning

Deep Learning
Deep Learning Papers Reading Roadmap
Deep Learning Papers Reading...
📃 Papers
📃 Papers
Zeta Alpha 
Search Engine for papers
Zeta Alpha...
Understanding
Neural Networks
Understanding...
 🧠 Neural Networks
 🧠 Neural Networks
Feedforward neural network
Feedforward neural network
Autoencoder
Autoencoder
Convolutional Neural Network
(CNN)
Convolutional Neural Network...
Generative Adversarial Network (GAN)
Generative Adversarial Netwo...
🏢 Architectures
🏢 Architectures
 🔧 Tools
 🔧 Tools
PyTorch
PyTorch

keep exploring and stay up-to-date

keep exploring and s...
Recurrent Neural Network
(RNN)
Recurrent Neural Network...
LSTM
LSTM
GRU
GRU
Tensorflow
Tensorflow
Loss Functions
Loss Functions
Activation Functions
Activation Functions
Weight Initialization
Weight Initialization
Vanishing / Exploding
Gradient Problem
Vanishing / Exploding...
Pooling
Pooling
Transformer
Transformer
Encoder
Encoder
Decoder
Decoder
Attention
Attention
Siamese Network
Siamese Network
Residual Connections
Residual Connections
Optimizers
Optimizers
 🧮 Training 
 🧮 Training 
Learning Rate Schedule
Learning Rate Schedule
Batch Normalization
Batch Normalization
Batch Size Effects
Batch Size Effects
Regularization
Regularization
Multitask Learning
Multitask Learning
Transfer Learning
Transfer Learning
Curriculum Learning
Curriculum Learning
SGD
SGD
Momentum
Momentum
Adam
Adam
AdaGrad
AdaGrad
Nadam
Nadam
RMSProp
RMSProp
Early Stopping
Early Stopping
Dropout
Dropout
Parameter Penalties
Parameter Penalties
Data Augmentation
Data Augmentation
Adversarial Training
Adversarial Training
Keras
Keras
MLFlow
MLFlow
Distillation
Distillation
⚖️ Model optimization
(advanced)
⚖️ Model optimizatio...
Neural Architecture
Search (NAS)
Neural Architecture...
Quantization
Quantization
Evolving Architectures / NEAT
Evolving Architectures / NEAT

🔎 Legend

Yellow boxes are key topics to study. Purple boxes are derivative topics. Blue boxes are tools to master. Boxes contain links to relevant learning resources.

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