ingoampt
INGOAMPT_machine learning _ Deep learning _learn German
131 posts
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ingoampt · 3 days ago
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GPU and Computing Technology Comparison 2024 - day 7
GPU and Computing Technology Comparison 2024 Exploring the Latest in GPU and Computing Technology: NVIDIA, Google Colab, Apple M4 Chip, and More In the rapidly evolving world of technology, GPUs (Graphics Processing Units) have become pivotal, extending far beyond their initial purpose of rendering graphics. Today, GPUs are foundational in fields such as machine learning, data analysis,…
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ingoampt · 4 days ago
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Fine-Tuning vs. Transfer Learning in Voice Synthesis
Fine-Tuning vs. Transfer Learning in Voice Synthesis Fine-Tuning vs. Transfer Learning: Adapting Voice Synthesis Models Introduction In the world of deep learning, transfer learning and fine-tuning are essential techniques that enable pre-trained models to quickly adapt to new tasks. These techniques are especially valuable in complex tasks like voice synthesis, where the model must capture the…
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ingoampt · 5 days ago
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Fine-Tuning in Deep Learning with a practical example - day 6
Understanding Fine-Tuning in Deep Learning Understanding Fine-Tuning in Deep Learning: A Comprehensive Overview Fine-tuning in deep learning has become a powerful technique, allowing developers to adapt pre-trained models to specific tasks without training from scratch. This approach is especially valuable in areas like natural language processing, computer vision, and voice cloning. In this…
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ingoampt · 6 days ago
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DeepNet – Scaling Transformers to 1,000 Layers new for 2024 - day 5
DeepNet – Scaling Transformers to 1,000 Layers DeepNet – Scaling Transformers to 1,000 Layers: The Next Frontier in Deep Learning Introduction In recent years, Transformers have become the backbone of state-of-the-art models in both NLP and computer vision, powering systems like BERT, GPT, and LLaMA. However, as these models grow deeper, stability becomes a significant hurdle. Traditional…
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ingoampt · 8 days ago
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Transformers seems most famous for deep learning on 2024 so lets learn it more - day 4
Transformers in Deep Learning (2024): Types, Advances, and Mathematical Foundations Transformers have transformed the landscape of deep learning, becoming a fundamental architecture for tasks in natural language processing (NLP), computer vision, and beyond. Since their inception in the 2017 paper “Attention is All You Need” by Vaswani et al., transformer architectures have continuously evolved,…
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ingoampt · 8 days ago
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You wanna use ChatGPT 4o by tokens instead o buying monthly subscription but you do not know how to implement on Mac Xcode ? Here we discuss how to Implement chatgpt API on Xcode On Mac on 2024 : (day3)
Introduction: Choosing Between ChatGPT Plus and Token-Based API for SwiftUI Integration When integrating OpenAI’s ChatGPT into your SwiftUI application, you have two primary options: subscribing to ChatGPT Plus or utilizing the ChatGPT API with token-based pricing. Each approach offers distinct advantages and considerations. ChatGPT Plus Subscription ChatGPT Plus is a subscription service priced…
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ingoampt · 10 days ago
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New on 2024 - 2025 are MLX and Transofermers so lets compare Custom Deep Learning Models for iOS with MLX on Apple Silicon vs. PyTorch - day 2
Building Custom Deep Learning Models for iOS with MLX on Apple Silicon vs. PyTorch New on 2024 – 2025 are MLX and Transofermers so lets compare Custom Deep Learning Models for iOS with MLX on Apple Silicon vs. PyTorch The development of deep learning applications for iOS has become increasingly sophisticated with Apple’s M-series chips, which allow for powerful local processing on mobile…
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ingoampt · 11 days ago
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Deep Learning in 2024: Continued Insights and Strategies - day 1
Deep Learning in 2024: Latest Models, Applications, and Monetization Strategies Deep Learning in 2024: Latest Models, Applications, and Monetization Strategies In 2024, deep learning continues to be at the forefront of innovation, influencing industries across various domains. For solo developers and iOS app creators, the year brings an array of models, frameworks, and profitable opportunities.…
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ingoampt · 16 days ago
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How Dalle Image Generator works ? - day 76
First check our previous article about what is Diffusion Model before reading this article DALL-E Blog Post How DALL-E Works: A Comprehensive Guide to Text-to-Image Generation DALL-E, developed by OpenAI, is a revolutionary model that translates text prompts into detailed images using a complex, layered architecture. The recent 2024 update to DALL-E introduces enhanced capabilities, like…
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ingoampt · 16 days ago
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Breaking Down Diffusion Models in Deep Learning – Day 75
Unveiling Diffusion Models: From Denoising to Generative Art The field of generative modeling has witnessed remarkable advancements over the past few years, with diffusion models emerging as a powerful class capable of generating high-quality, diverse images and other data types. Rooted in concepts from thermodynamics and stochastic processes, diffusion models have not only matched but, in some…
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ingoampt · 18 days ago
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Understanding Unsupervised Pretraining Using Stacked Autoencoders
Understanding Unsupervised Pretraining Using Stacked Autoencoders Part 1: Understanding Unsupervised Pretraining Using Stacked Autoencoders Introduction: Tackling Complex Tasks with Limited Labeled Data When dealing with complex supervised tasks but lacking sufficient labeled data, one effective solution is unsupervised pretraining. In this approach, a neural network is first trained to perform…
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ingoampt · 19 days ago
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Unlock the Secrets of Autoencoders, GANs, and Diffusion Models – Why You Must Know Them? -Day 73
Autoencoders, GANs, and Diffusion Models – A Deep Dive Part 1: Understanding Autoencoders, GANs, and Diffusion Models – A Deep Dive In this post, we’ll explore three key models in machine learning: Autoencoders, GANs (Generative Adversarial Networks), and Diffusion Models. These models, used for unsupervised learning, play a crucial role in tasks such as dimensionality reduction, feature…
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ingoampt · 26 days ago
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What is NLP and the Math Behind It? - day 71
Understanding NLP and the Math Behind It What is NLP and the Math Behind It? Understanding Transformers and Deep Learning in NLP Introduction to NLP Natural Language Processing (NLP) is a crucial subfield of artificial intelligence (AI) that focuses on enabling machines to process and understand human language. Whether it’s machine translation, chatbots, or text analysis, NLP helps bridge the…
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ingoampt · 29 days ago
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How ChatGPT Work Step by Step - day 70
ChatGPT Step-by-Step Process Understanding How ChatGPT Processes Input: A Step-by-Step Guide Table of Contents Introduction Step 1: Input Tokenization Step 2: Token Embedding Step 3: Positional Encoding Step 4: Input to the Transformer Step 5: Multi-Head Self-Attention Mechanism Step 6: Add & Normalize Step 7: Position-wise Feedforward Network Step 8: Stacking Multiple Transformer Layers Step…
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ingoampt · 1 month ago
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Leveraging Scientific Research to Uncover How ChatGPT Supports Clinical and Medical Applications - day 68
Understanding How ChatGPT Works: A Step-by-Step Guide Understanding How ChatGPT Works: A Step-by-Step Guide ChatGPT, developed by OpenAI, is a sophisticated language model that can generate human-like responses to various queries. But how exactly does it work? In this post, I’ll walk you through the core components of ChatGPT’s functionality, using examples, tables, and figures to make the…
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ingoampt · 1 month ago
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What is BERT(Bidirectional Encoder Representations from Transformers) - day 67
Understanding BERT: How It Works and Its Role in NLP Understanding BERT: How It Works and Why It’s Transformative in NLP BERT (Bidirectional Encoder Representations from Transformers) is a foundational model in Natural Language Processing (NLP) that has reshaped how machines understand language. Developed by Google in 2018, BERT brought significant improvements in language understanding tasks by…
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ingoampt · 1 month ago
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Transformers Deep Learning - day 66
Understanding Transformers: The Backbone of Modern NLP Understanding Transformers: The Backbone of Modern NLP Introduction Transformers have significantly transformed the field of Natural Language Processing (NLP). Originally introduced in the 2017 paper “Attention is All You Need” by Vaswani et al., Transformers replaced recurrent (RNN) and convolutional (CNN) architectures with an entirely…
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