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Deep Learning News
Medium
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Automated Fake News Detection
- Automated fake news detection is revolutionizing media trustworthiness by tackling bias and misinformation with advanced AI models.
- Automated fake news detection aims to combat the spread of misinformation and influence on public opinion.
- The challenge lies in creating algorithms that can identify false information while considering the ethical implications.
- Technology plays a crucial role in ensuring media reliability and restoring trust in news sources.
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Medium
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Mastering Productivity with the Pomodoro Technique: My Journey
- The Pomodoro Technique is a time management method developed by Francesco Cirillo in the late 1980s.
- It involves working in focused 25-minute intervals called Pomodoros, followed by short breaks.
- Tasks are broken down into smaller, manageable pieces for better clarity and focus.
- The technique improves productivity, focus, work-life balance, and energy levels.
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From room-sized computers to palm-sized industrial computers
- The article discusses the features of the CM4, a palm-sized industrial computer.
- It is about a third of the size of a typical credit card and comes with various features.
- These features include Gigabit Ethernet, M.2 B KEY/Mini-PCIe for 5G/4G/LoRa module, Nano-SIM card slot, USB 2.0 ports, RS485 and CAN interfaces, MIPI CSI-2 camera connector, HDMI with 4K output, RTC battery slot, and more.
- Important notes to consider are regarding hot plugging, fan voltage, writing CM4 via Type C interface, power supply, and avoiding simultaneous power from 12V DC and 5V Type C.
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Medium
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How to Use Transfer Learning the Right Way: A Beginner’s Guide
- Transfer learning is a technique in machine learning that involves using knowledge gained from solving one problem to help solve a different but related problem.
- It allows models to leverage pre-trained neural networks and the experience acquired from solving previous tasks.
- For example, if a neural network has been trained to classify products, it can be used as a starting point for training a new network to classify different types of products.
- Transfer learning is a powerful tool that can save time and computational resources while still achieving high accuracy in new tasks.
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Medium
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Breaking Down Complex ML Models: Explaining LSTM, CNN, and Transformers for Beginners
- LSTM is a memory system for machines, helping them remember important information over time. It uses special 'gates' to decide what information to keep, update, or forget.
- CNNs analyze images by breaking them down into smaller pieces and looking for patterns. They use layers of filters to detect features and recognize objects.
- Transformers can understand entire documents at once, rather than reading word by word. They use attention mechanism to focus on important parts of the input.
- These models are used in various applications like recommendation systems and virtual assistants, making life easier and more connected.
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Medium
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How Attention in Neural Networks Works (and Why It’s Amazing)
- Attention mechanisms in AI help machines determine what's important and make smarter decisions.
- Attention allows AI to focus on specific parts of input, like highlighting important words in a sentence or key details in an image.
- Attention scores are assigned to different parts, with higher scores indicating more focus.
- Attention helps AI handle complex inputs and improve accuracy in tasks like translation or understanding sentences.
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Medium
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Computer Vision 101: A Beginner’s Guide to Visual Intelligence
- Computer Vision is the interpretation and processing of visual data using mathematical techniques.
- Linear algebra and geometry form the mathematical foundation of computer vision.
- Point clouds and volumetric methods are used to represent objects in 3D space.
- Computer vision has applications in autonomous vehicles, augmented reality, urban planning, and 3D printing.
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Medium
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ModernBERT: A Masked Language Modeling Exploration
- ModernBERT is a novel language model that pushes the boundaries of natural language processing.
- It is trained on 2 trillion tokens with an 8192 sequence length and outperforms existing encoder models regarding speed, memory efficiency, and performance.
- ModernBERT incorporates modern architecture and training techniques such as GeGLU, ROPE, and alternating local-global attention.
- This code snippet demonstrates the usage of ModernBERT for masked language modelling and its application in various NLP tasks.
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Medium
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A Simple Way to Earn Up to $547 Daily Online
- The AMZ Money Machine is a program that allows users to earn passive income through Amazon Kindle Publishing
- Users can upload pre-made books and start earning profits without the need for writing or creating content from scratch
- The system automates the process and drives traffic to the users' listings, resulting in consistent earnings
- With minimal effort, users can earn up to $547.93 daily, with each book typically generating earnings ranging from $20 to $50
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Medium
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212
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Why AI Integration in Boardrooms is Reshaping Governance
- AI integration in boardrooms is reshaping governance.
- AI tools like Aiden Insight provide real-time insights for decision-making.
- AI technology enhances governance by leveraging comprehensive data.
- AI balances human intuition and improves the decision-making process.
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Medium
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The Amazing Power of Modern Graphics Cards
- Graphics cards, or GPUs, are the unsung heroes of modern computing, powering various applications.
- GPUs excel at performing calculations on massive amounts of data simultaneously, like a cargo ship efficiently transporting goods.
- The GPU, with billions of transistors and thousands of cores, is the heart of a graphics card.
- The latest memory technology, GDDR6X, enables lightning-fast data transfer in graphics cards.
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Medium
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Embeddings Unveiled: The Hidden Language of Data Science (with python examples)
- Embeddings solve the problem of traditional approaches to data representation.
- There are various approaches for embedding models like Word2Vec, GloVe, FastText.
- LSA is a widely-used approach that uses Singular Value Decomposition (SVD) for dimensionality reduction.
- Probabilistic Topic Modeling (PTM) is a popular technique that uses generative models to determine the latent topics in a corpus of documents.
- ELMo uses a bidirectional language model (BiLM) to create dynamic and contextualized embeddings for words.
- BERT is a pretrained language model designed to understand the context of a word in relation to the words surrounding it.
- GPT is primarily designed for text generation tasks and uses the decoder part of the Transformer architecture.
- T5 is a model that treats every NLP task as a text-to-text problem.
- GPT-3 is one of the largest and most influential foundation models in NLP and is autoregressive.
- PaLM is built on the Pathways architecture, which enables it to learn from a more diverse set of tasks.
- LaMDA is specially designed for dialogue generation and training to improve the quality of conversation in open-ended dialogues.
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Medium
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393
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I trained a small transformer model from scratch!
- The author trained a Large Language Model (LLM) from scratch using a small dataset of Telugu lyrics.
- The model was scaled down to 6.58M parameters and trained for next token prediction.
- Training the model took approximately 53 minutes per epoch and a total of 9 hours and 30 minutes.
- Despite overfitting to the training data, the model generated decent Telugu words during inference.
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Medium
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Day 54: RNN Applications — Text Processing, Time-Series Forecasting
- Recurrent Neural Networks (RNNs) have revolutionized text processing and time-series forecasting.
- RNNs excel in text processing by capturing contextual relationships in sequential data.
- In time-series forecasting, RNNs analyze temporal dependencies to understand trends and patterns.
- Leveraging LSTMs and other advanced techniques, RNNs unlock potential in real-world problems.
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Medium
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Building AI Web Apps: A Practical Guide to HuggingFace Spaces and Gradio APIs
- In this tutorial, we'll take your trained model and make it accessible to anyone in the world through Hugging Face Spaces.
- Hugging Face adds that extra magic specifically designed for machine learning projects. When combined with Gradio, a powerful tool for creating web interfaces, your sophisticated model becomes a user-friendly application that anyone can interact with.
- To create a project, we navigate to https://huggingface.co/spaces and give it a descriptive name like food_classifier.
- We then choose Gradio as our "Space SDK." Let's choose a "Blank" Gradio template.
- Preparing Our Code with Jupyter Notebook and nbdev. We create a new Jupyter Notebook to write the code that will power our Gradio interface on Hugging Face Spaces.
- We then install Gradio using this simple command: !pip install gradio==4.4.1
- We’ve seen that our model can accurately predict the class of individual images. Now, let’s encapsulate this prediction logic into a function that will be the core of our Gradio application.
- Gradio is a fantastic library that allows us to quickly create interactive web interfaces for our machine learning models, making them accessible and engaging.
- With just a few steps, we’ve gone from a Jupyter Notebook to a live, deployed application. You can see the result right in your browser at our HuggingFace Space: huggingface.co/spaces/joonieoops/food_classifier.
- If you’re looking to go beyond Gradio’s built-in UI, you’re in luck! Hugging Face Spaces provides a way to interact with your model through a set of APIs.
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