AI With Python – Generative AI
Generative AI re creative models that are capable to generate fresh content, typically encompassing images, text, audio, or various data form. This area of AI is dedicated to producing novel and diverse outputs based on learned patterns and structures.
Image Generation Architectures
Image generation architectures refer to specialized models or neural network structures crafted for the purpose of generating realistic images. These architectures utilize generative models to create visual content that is both realistic and diverse. Below are some noteworthy examples of image generation architectures:
- Variational Autoencoders
- Generative Adversarial Networks (GANs)
- Conditional GAN (cGAN)
- Wasserstein GAN (WGAN)
- Progressive GAN
- BigGAN
- CycleGAN
- VQ-VAE-2 (Vector Quantized Variational Autoencoder)
- Style GANs
Text Generation Architectures
Text generation architectures refer to specialized models or neural network structures created for the purpose of generating fresh textual content. These architectures utilize generative models to produce text that is both coherent and contextually appropriate. Some of the text generation models are:
- Transformers
- GPT (Generative Pre-trained Transformer)
- BERT (Bidirectional Encoder Representations from Transformers)
- T5 (Text-to-Text Transfer Transformer)
- CTRL (Conditional Transformer Language Model)
- UniLM (Unified Language Model)
Audio Generation Architectures
Architectures dedicated to audio generation are specialized neural network models crafted for the purpose of generating novel audio content. These structures utilize generative models to create sound sequences that are realistic. Some of the prominent audio generation articles are:
- WaveNet
- WaveGAN
- Tacotron2
- EnCodec
- AudioLM
- Deep Voice
We have navigated through the AI journey and covered interesting topics of machine learning (ML), deep learning (DL), computer vision (CV), generative AI and natural language processing (NLP). Python plays an important role in crafting of intelligent solutions with elegance and efficiency. Python AI stand at the intersection of code and intelligence.
AI With Python Tutorial
In this AI with Python tutorial, you’ll explore the fundamental and advanced concepts of artificial intelligence (AI) using the Python programming language. Whether you’re a complete beginner or an experienced professional, this tutorial is tailored to meet your learning needs, offering a step-by-step approach to mastering AI techniques with Python.
From understanding basic concepts to exploring advanced algorithms and applications, this tutorial equips you with the essential skills and knowledge to dive into the exciting world of AI. Whether you’re looking your build your career in AI or enhance your existing skills, this tutorial provides a solid foundation for your AI journey.
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