Tutorials > Generative Ai (English Version) Unleashing Next-Gen Ai
Generative Ai (English Version) Unleashing Next-Gen AiDate: 3 May 2023 | Posted by: voska89 |
![]() Published 4/2023 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 3.86 GB | Duration: 7h 19m The Good, the Bad and the Ugly Free Download What you'll learn Generative AI definition, areas of applications, mappings like txt2txt, img2txt, txt2img and txt2voice How ChatGPT works, and the underlying tech behind like GPT, Large-Scale Language Models (LLM) and Transformers How Latent Diffusion, StableDiffusion and DALL-E systems work Generative Adversarial Networks (GANs) and Variational Auto Encoder (VAE) The good, bad and ugly faces of GenAI, and how to adapt to the new tech Build ChatGPT clone using OpenAI API and Streamlit Build NLP applications using OpenAI API like Summarization, Text Classification and fine tuning GPT models Build NLP applications using Huggingface transformers library like Language Models, Summarization, Translation, QA systems and others Build Midjourney clone application using OpenAI DALL-E and StableDiffusion on Huggingface Requirements AI, ML and Deep Learning foundations NLP: RNN, LSTM, Transformers basics CV: ConvNets Description Hello and Welcome to a new Journey in the vast area of Generative AIGenerative AI is changing our definition of the way of interacting with machines, mobiles and computers. It is changing our day-to-day life, where AI is an essential component.This new way of interaction has many faces: the good, the bad and the ugly.In this course we will sail in the vast sea of Generative AI, where we will cover both the theoretical foundations of Generative models, in different modalities mappins: Txt2Txt, Img2Txt, Txt2Img, Img2Txt and Txt2Voice and Voice2Text. We will discuss the SoTA models in each area at the time of this course. This includes the SoTA technology of Transformers, Language models, Large LM or LLM like Generative Pre-trained Transformers (GPT), paving the way to ChatGPT for Text Generation, and GANs, VAE, Diffusion models like DALL-E and StabeDiffusion for Image Generation, and VALL-E foe Voice Generation.In addition, we will cover the practical aspects, where we will build simple Language Models, Build a ChatGPT clone using OpenAI APIs where we will take a tour in OpenAI use cases with GPT3.5 and ChatGPT and DALL-E. In addition we will cover Huggingface transformers and StableDiffusion.Hope you enjoy our journey! Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Course overview Section 2: What is Generative AI? Lecture 3 What is Generative AI? Lecture 4 Generative vs. Discriminative models Lecture 5 Why Generative models? Lecture 6 Encoder-Decoder design pattern Lecture 7 GenAI modalities mappings Section 3: Txt2Txt GenAI Lecture 8 Unimodal mappings: Txt2txt and Language models Lecture 9 Statistical Language Models (SLM) Lecture 10 Neural Language Models (NLM) - Char level Lecture 11 Neural Language Models (NLM) - Word level Lecture 12 SLM and NLM in Python and Keras Lecture 13 Seq2seq models Lecture 14 Seq2seq + Attention models Lecture 15 Transformers Lecture 16 Huggingface Transformer Pipeline Lecture 17 Large-Scale Language Models (LLM) - Transfer Learning in NLP Lecture 18 Pre-trained Transformers Lecture 19 BERT Lecture 20 GPT Lecture 21 ChatGPT Lecture 22 OpenAI API Lecture 23 GPT-3 Finetuning Lecture 24 GPT-3 Chatbot Lecture 25 ChatGPT Clone in Google Colab Lecture 26 ChatGPT Clone in Streamlit Lecture 27 ChatGPT Clone Excercise Section 4: Img2Img GenAI Lecture 28 Img2Img Encoder-Decoder Lecture 29 Auto Encoder (AE) Lecture 30 AE Visualization Lecture 31 Variational Auto Encoder (VAE) Lecture 32 Conditional VAE Lecture 33 Coding AE in Keras Lecture 34 Generative Adversarial Nets (GANs) Lecture 35 Generating images from GANs Lecture 36 Training GANs Lecture 37 Coding GAN training in Keras Lecture 38 DCGAN Lecture 39 Conditional GANs Lecture 40 AttributeGAN Lecture 41 How Good are GANs today? Lecture 42 Domain adaptation with pix2pix and CycleGAN Section 5: Multi-modal GenAI Lecture 43 Multimodal Txt2Img generation Lecture 44 Diffusion models Lecture 45 Latent Diffusion Models (LDM) Lecture 46 CLIP Lecture 47 StableDiffusion Lecture 48 Online tools for txt2img: DreamStudio and Midjourney Lecture 49 OpenAI API - DALL-E Lecture 50 Huggingface - StableDiffusion Lecture 51 Excercise - Midjourney clone Lecture 52 Img2Txt generation - Image Captioning Lecture 53 Txt2Voice generation - VALL-E Section 6: The good, the bad and the ugly Lecture 54 The Good Lecture 55 The Bad Lecture 56 The Ugly Lecture 57 What should we do? Section 7: Conclusion Lecture 58 Conclusion Section 8: Material Lecture 59 Material AI/ML Practitioners, Developers, Engineers and Researchers,NLP Engineers or Researchers,CV Engineers or Researchers,Data Scientists Homepage DOWNLOAD LINK Rapidgator brpdf.G.A.E.V.U.N.A.part2.rar.html brpdf.G.A.E.V.U.N.A.part1.rar.html brpdf.G.A.E.V.U.N.A.part4.rar.html brpdf.G.A.E.V.U.N.A.part3.rar.html Uploadgig brpdf.G.A.E.V.U.N.A.part3.rar brpdf.G.A.E.V.U.N.A.part1.rar brpdf.G.A.E.V.U.N.A.part2.rar brpdf.G.A.E.V.U.N.A.part4.rar NitroFlare brpdf.G.A.E.V.U.N.A.part1.rar brpdf.G.A.E.V.U.N.A.part4.rar brpdf.G.A.E.V.U.N.A.part2.rar brpdf.G.A.E.V.U.N.A.part3.rar Links are Interchangeable - Single Extraction See full article |