Data Science & Developer Roadmaps with Chat & Free Learning Resources

Deep Learning Roadmap

Below you’ll find the Deep Learning roadmap - a step-by-step guide on how to become a Deep Learning Engineer. This roadmap covers topics like Neural Networks, ML/ DL architecture, and Models Optimalization.

This not a beginners track! Make sure that you have completed the other roadmaps before jumping on this track.

All boxes are clickable and provide you with AI-powered explanations and free learning resources. You can also chat with our 🤖 bot when you have any question about the topics on this roadmap.

NeuralNetworksArchitecturesPapersTrainingToolsModel OptimizationKeep exploring!Deep Learnin Papers Reading RoadmapZeta Alpha Search Engine for PapersUnderstanding Neural NetworksLoss FunctionsActivation FunctionsWeight InitializationVanishing & Exploding GradientFeedforward Neural NetworkAutoencoderConvolutional Neural Network (CNN)Recurrent Neural Network (RNN)TransformersSiamese NetworkGenerative Adversarial Network (GAN)Evolving Architectures / NEATResidual ConnectionsPoolingLSTMGRUEncoderDecoderAttentionOptimizerLearning Rate ScheduleBatch NormalizationBatch Size EffectRegularizationMultitask LearningTransfer LearningCurriculum LearningSGDMomentumAdamAdaGradNadamRMSPropEarly StoppingDropoutParameter PenaltiesData AugmentationAdversarial TrainingTensorflowPyTorchKerasMLflowDistillationQuantizationNeural Architecture Search (NAS)Deep Learning