Add mindmap
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Dmitri Soshnikov
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Mindmap.md
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Mindmap.md
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# AI
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## Introduction to AI
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- [AI Definition](https://github.com/microsoft/AI-For-Beginners/blob/main/1-Intro/README.md#different-approaches-to-ai)
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- [History of AI](https://github.com/microsoft/AI-For-Beginners/blob/main/1-Intro/README.md#different-approaches-to-ai)
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- [Approaches to AI](https://github.com/microsoft/AI-For-Beginners/blob/main/1-Intro/README.md#different-approaches-to-ai)
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## Sybmbolic AI
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- Knowledge Representation
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- Expert Systems
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## [Neural Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/README.md)
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- [Perceptron](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/03-Perceptron/README.md)
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- [Multi-Layered Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/04-OwnFramework/README.md)
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- [Intro to Frameworks](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/README.md)
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- [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb)
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- [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/IntroKerasTF.md)
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- [Overfitting](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/Overfitting.md)
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## Computer Vision
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- Intro to CV. OpenCV
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- Convolutional Networks
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- Training Tricks
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- Architectures
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- Trasnsfer Learning
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- Autoencoders and VAEs
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- Generative Adversarial Networks
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- Object Detection
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- Segmentation
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## Natural Language Processing
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- Text Representation
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- Bag of Words
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- TF/IDF
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- Semantic Embeddings
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- Word2Vec
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- GloVE
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- Language Modeling
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- Recurrent Neural Networks
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- Generative Recurrent Networks
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- Transformers and BERT
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- Named Entity Recognition
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- Text Generation and GPT
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## Other Techniques
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- Genetic Algorithms
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- Deep Reinforcement Learning
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- Multi-Agent Systems
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## AI Ethics
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@ -87,13 +87,14 @@ For a gentle introduction to *AI in the Cloud* topic you may consider taking the
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<tr><td>1</td><td>Multi-Modal Networks, CLIP and VQGAN</td><td><a href="X-Extras/1-MultiModal/README.md">Text</a></td><td></td><td></td><td></td></tr>
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</table>
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**[Mindmap of the Course](etc/Mindmap.html)**
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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.
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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.
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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.
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# Getting Started
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# Multi-Modal Networks
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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.
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## Contrastive Image Pre-Training (CLIP)
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# AI
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## Introduction to AI
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- [AI Definition](https://github.com/microsoft/AI-For-Beginners/blob/main/1-Intro/README.md#different-approaches-to-ai)
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- [History of AI](https://github.com/microsoft/AI-For-Beginners/blob/main/1-Intro/README.md#different-approaches-to-ai)
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- [Approaches to AI](https://github.com/microsoft/AI-For-Beginners/blob/main/1-Intro/README.md#different-approaches-to-ai)
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## Sybmbolic AI
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- Knowledge Representation
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- Expert Systems
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## [Neural Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/README.md)
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- [Perceptron](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/03-Perceptron/README.md)
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- [Multi-Layered Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/04-OwnFramework/README.md)
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- [Intro to Frameworks](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/README.md)
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- [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb)
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- [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/IntroKerasTF.md)
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- [Overfitting](https://github.com/microsoft/AI-For-Beginners/blob/main/3-NeuralNetworks/05-Frameworks/Overfitting.md)
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## [Computer Vision](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/README.md)
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- Intro to CV. OpenCV
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- [Convolutional Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/07-ConvNets/README.md)
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- [Architectures](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/07-ConvNets/CNN_Architectures.md)
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- [Trasnsfer Learning](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/08-TransferLearning/README.md)
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- [Training Tricks](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/08-TransferLearning/TrainingTricks.md)
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- [Autoencoders and VAEs](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/09-Autoencoders/README.md)
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- [Generative Adversarial Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/4-ComputerVision/10-GANs/README.md)
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- Object Detection
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- Segmentation
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## [Natural Language Processing](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/README.md)
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- [Text Representation](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/13-TextRep/README.md)
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- Bag of Words
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- TF/IDF
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- [Semantic Embeddings](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/14-Embeddings/README.md)
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- Word2Vec
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- GloVE
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- [Language Modeling](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/15-LanguageModeling)
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- [Recurrent Neural Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/16-RNN/README.md)
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- LSTM
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- GRU
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- [Generative Recurrent Networks](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/17-GenerativeNetworks/README.md)
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- [Transformers and BERT](https://github.com/microsoft/AI-For-Beginners/blob/main/5-NLP/18-Transformers/README.md)
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- Named Entity Recognition
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- Text Generation and GPT
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## Other Techniques
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- [Genetic Algorithms](https://github.com/microsoft/AI-For-Beginners/blob/main/6-Other/21-GeneticAlgorithms/README.md)
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- Deep Reinforcement Learning
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- [Multi-Agent Systems](https://github.com/microsoft/AI-For-Beginners/blob/main/6-Other/23-MultiagentSystems/README.md)
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## [AI Ethics](https://github.com/microsoft/AI-For-Beginners/blob/main/7-Ethics/README.md)
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## Extras
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- Multimodal Networks
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- CLIP
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- DALL-E
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- VQ-GAN
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