+**[Mindmap of the Course](etc/Mindmap.html)**
+
Each lesson contains some pre-reading material (linked as **Text** above), and some executable Jupyter Notebooks, which are often specific to the framework (**PyTorch** or **TensorFlow**). The executable notebook also contains a lot of theoretical material, so to understand the topic you need to go through at least one version of the notebooks (either PyTorch or TensorFlow). There are also **Labs** available for some topics, which give you an opportunity to try applying the material you have learnt to a specific problem.
Some sections also contain links to **MS Learn** modules that cover related topics. Microsoft Learn provides a convenient GPU-enabled learning environment, although in terms of content you can expect this curriculum to go a bit deeper.
Course sections also include the links to **PAT**s - Progress Assessment Tool, a list of items that you are likely to get to know after completing the module. You can review it and assess your progress on the course yourself.
-
# Getting Started
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+# Multi-Modal Networks
+
+After the success of transformer models for solving NLP tasks, there were many attempts to apply the same or similar architectures to computer vision tasks. Also, there is a growing interest in building models that would *combine* vision and natural language capabilities. One of such attempts was done by OpenAI, which is called CLIP.
+
+## Contrastive Image Pre-Training (CLIP)
+
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+Markmap
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+# AI
+
+## Introduction to AI
+ - [AI Definition](https://github.com/microsoft/AI-For-Beginners/blob/main/1-Intro/README.md#different-approaches-to-ai)
+ - [History of AI](https://github.com/microsoft/AI-For-Beginners/blob/main/1-Intro/README.md#different-approaches-to-ai)
+ - [Approaches to AI](https://github.com/microsoft/AI-For-Beginners/blob/main/1-Intro/README.md#different-approaches-to-ai)
+
+## Sybmbolic AI
+ - Knowledge Representation
+ - Expert Systems
+
+## [Neural Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/README.md)
+ - [Perceptron](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/03-Perceptron/README.md)
+ - [Multi-Layered Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/04-OwnFramework/README.md)
+ - [Intro to Frameworks](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/README.md)
+ - [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb)
+ - [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/IntroKerasTF.md)
+ - [Overfitting](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/Overfitting.md)
+
+## [Computer Vision](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/README.md)
+ - Intro to CV. OpenCV
+ - [Convolutional Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/07-ConvNets/README.md)
+ - [Architectures](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/07-ConvNets/CNN_Architectures.md)
+ - [Trasnsfer Learning](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/08-TransferLearning/README.md)
+ - [Training Tricks](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/08-TransferLearning/TrainingTricks.md)
+ - [Autoencoders and VAEs](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/09-Autoencoders/README.md)
+ - [Generative Adversarial Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/10-GANs/README.md)
+ - Object Detection
+ - Segmentation
+
+## [Natural Language Processing](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/README.md)
+ - [Text Representation](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/13-TextRep/README.md)
+ - Bag of Words
+ - TF/IDF
+ - [Semantic Embeddings](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/14-Embeddings/README.md)
+ - Word2Vec
+ - GloVE
+ - [Language Modeling](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/15-LanguageModeling)
+ - [Recurrent Neural Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/16-RNN/README.md)
+ - LSTM
+ - GRU
+ - [Generative Recurrent Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/17-GenerativeNetworks/README.md)
+ - [Transformers and BERT](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/18-Transformers/README.md)
+ - Named Entity Recognition
+ - Text Generation and GPT
+## Other Techniques
+ - [Genetic Algorithms](https://github.com/microsoft/AI-For-Beginners/blob/main/6-Other/21-GeneticAlgorithms/README.md)
+ - Deep Reinforcement Learning
+ - [Multi-Agent Systems](https://github.com/microsoft/AI-For-Beginners/blob/main/6-Other/23-MultiagentSystems/README.md)
+
+## [AI Ethics](https://github.com/microsoft/AI-For-Beginners/blob/main/7-Ethics/README.md)
+## Extras
+ - Multimodal Networks
+ - CLIP
+ - DALL-E
+ - VQ-GAN
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