Deep Learning
( 25 Modules )

Modul #1
Introduction to Deep Learning
Iwwersview of Deep Learning, History, and Applications

Modul #2
Mathematical Prerequisites
Review of linear Algebra, Calcus, and Probability Theory

Modul #3
Neural Networks Basics
Aféierung zu kënschtlechen neuralen Netzwierker, Perceptronen a Multilayer Perceptronen

Modul #4
Aktivatiounsfunktiounen a Réckpropagatioun
Aktivatiounsfunktiounen, Réckpropagatioun a Gradient Ofstamung

Modul #5
Neural Netzwierker bauen an trainéieren
Hands-on Erfahrung mam Bau an Training neural Netzwierker mat engem Deep Learning Kader

Modul #6
Convolutional Neural Networks (CNNs)
Aféierung zu CNNs, convolutional Schichten, a Poolschichten

Modul #7
CNN Architectures
AlexNet, VGGNet, GoogLeNet, a ResNet Architekturen

Modul #8
Transfer Learning and Fine-tuning
Gebrauch vu viraus trainéierten CNN Modeller a Feintuning fir Bildklassifikatiounsaufgaben

Modul #9
Recurrent Neural Networks (RNNs)
Aféierung zu RNNs, einfache RNNs, an LSTM Netzwierker

Modul #10
RNN Architectures
GRU, Bidirectional RNNs, an Encoder-Decoder Modeller

Modul #11
Sequence-to-Sequence Modeller
Maschinn Iwwersetzung, Chatbots, a Sequenz-zu-Sequenz Modeller

Modul #12
Generative Modeller
Aféierung zu generativen Modeller, GANs, a VAEs

Modul #13
Autoencoders a Variational Autoencoders
Dimensionalitéitsreduktioun, Autoencoder a VAEs

Modul #14
Generative Adversarial Networks (GANs)
GANs, DCGANs, and conditional GANs

Modul #15
Deep Reinforcement Learning
Aféierung zum Verstäerkungsléieren, Q-Learning, a Politikgradienten

Modul #16
Deep Reinforcement Learning Algorithms
DDPG, Actor-Critic Methods, an AlphaGo

Modul #17
Unsupervised Learning and Clustering
K-Mëttel, hierarchesch Clustering, an Dimensiounsreduktioun

Modul #18
Deep Learning for Natural Language Processing
Word Embeddings, Language Models, and Text Classification

Modul #19
Opgepasst Mechanismen
Opmierksamkeet an NLP, Transformatoren, a BERT

Modul #20
Deep Learning for Computer Vision
Object Detection, Segmentation, and Tracking

Modul #21
Deep Learning Frameworks
TensorFlow, PyTorch, a Keras

Modul #22
Model Evaluatioun an Hyperparameter Tuning
Model Evaluatiounsmetriken, Hyperparameter Tuning a Kräizvalidatioun

Modul #23
Deep Learning Deployment and Production
Model Deployment, Model Serving, and Production

Modul #24
Ethik a Fairness am Deep Learning
Ethesch Considératiounen, Bias, a Fairness an Deep Learning Modeller

Modul #25
Cours Ofschloss & Conclusioun
Planung nächst Schrëtt an Deep Learning Carrière

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