Running large language models locally on a laptop is becoming increasingly feasible, and Ollama makes it accessible. The key to a good experience is choosing a model that matches your laptop’s hardware, primarily its RAM… Ollama models that can be run on a laptop
LangChain is an open-source framework designed to simplify the creation of applications powered by large language models (LLMs). Available in both Python and JavaScript, it provides a modular and extensible architecture that allows developers to… LangChain: The Powerhouse Behind Intelligent Language Applications
LlamaIndex is a powerful and flexible open-source data framework designed to connect custom data sources to large language models (LLMs). In essence, it acts as a crucial bridge, enabling developers to build applications that can… LlamaIndex: Bridging the Gap Between Your Data and Large Language Models
Resubmitting a rejected paper is a common part of the academic publishing process. Approaching it systematically can dramatically increase your chances of success at a new venue. Here are the key things to note, broken… Importance Things to Notice when Resubmitting a Rejected Paper
In the rapidly advancing world of artificial intelligence, Large Language Models (LLMs) have emerged as powerful tools capable of generating human-like text, translating languages, and answering questions with remarkable fluency. However, these sophisticated models are… The Specter in the Machine: Understanding Hallucinations in Large Language Models
Retrieval-Augmented Generation (RAG) is a powerful technique that enhances the capabilities of Large Language Models (LLMs) by connecting them to external knowledge sources. According to Google Developer website, EmbeddingGemma is a compact, open‑source embedding model… RAG with EmbeddingGemma with Python Code using Ollama
Each of the following templates is followed by a download link on Xmind. To download, click the link, and then click on the “…” button on the top right corner of the page. Tables with… Professional Xmind chart templates for writing Grants, Proposals, etc.
The AdamW method was proposed in the paper “Decoupled Weight Decay Regularization” by Ilya Loshchilov and Frank Hutter. While the paper was officially published at the prestigious International Conference on Learning Representations (ICLR) in 2019,… AdamW optimization and implementation in PyTorch
Tempted to use AI for your literature review? Think about the critical risks, including factual ‘hallucinations,’ fabricated citations, subtle plagiarism, and incorrect attributions. Protect your research and academic integrity.
In the world of computer vision, we’re always chasing two things: better accuracy and faster training. The conventional wisdom is to use the largest, highest-quality images you can from the very beginning. But what if… Train AI Models Faster and Better: The Power of Progressive Resizing
“You said pooling operations in Convolutional Neural Networks (CNNs) are like the magical zoom-out buttons.” “They reduce the size of feature maps while keeping the juicy bits of information. But how?” Peter asked. “There are… Types of Pooling operations
“Professor, why is CNN so effective?” “CNNs don’t just look at the whole image like a confused tourist—they zoom in on tiny patches (called kernels) and analyze them like Sherlock Holmes inspecting clues.” “Ok. This… Why CNNs are so effective
“What’s CNN workflow?” Alex asked. Peter replied, “If we have an input image represented as a tensor, like a 32×32 pixel image with 3 color channels (Red, Green, Blue) would have a shape of 32x32x3.”… The CNN Workflow
I’m building a super tall tower out of Lego blocks. Each block is a layer in a neural network. The taller the tower, the more complex patterns it can learn. But the problem is “Tall… ResNet – Residual Network
“Hey Alex, do you know what AlexNet is?” The little spirit asked Alex. “AlexNet is a game changer. Many years ago, everyone were using basic machine learning models to recognize images — and they were… AlexNet: The CNN That Changed Everything
“Wow. So this is the canvas that can do image classification and object detection?” Vixel asked. “Yes, I am VGG. VGG stands for Visual Geometry Group.” the Canvas replied. “More exactly, I’m VGG19, which means… VGGNet in the Magic Canvas
“Hey, Kernel. You work for Mr. Convolution, right? What do you do there?” The pixelated giant asked, to which the young Kernel response, “A convolution is a mathematical operation that blends two functions to produce… convolutional operations and convolutional neural networks (CNNs) — the backbone of modern computer vision
“I love sortering, especially beautiful mushrooms like this.” Jon thought “But I heard something on object detection trying to micmic human ability. It combines object localization to create bounding boxes around each object and then… Object Detection
“The cat is so cute, but not the carpet! I want to grab the cat area only.” “What should I do now, Mr. Crystal?” Kevin asked, to which the magic crystal replied, “You can do… Segmentation by Thresholding: Techniques and Python Implementation
“The world was a dazzling mosaic of colors and shapes, but I wonder if the magical computer to see it differently.” The little fairy thought and flew to the house of the Great Wizard. “It’s… Convolution & Filtering
“Professor Elara,” chirped the little kid, “Can show me the magic of Image Transformations?” and Professor Elara blinked slowly. “Ok. We begin with Scaling.” With a gentle wave of her wing, Professor Elara conjured a… Image Transformations for Data Augmentation
Pixels are the smallest units of a digital image — think of them as the individual tiles in a mosaic. Each pixel holds color and intensity information, and by manipulating these values, we can transform… Pixel Operations
In a realm painted with light and shadow, there lived tiny sprites of light called Pixels. They were the weavers of the visual world, each a tiny, glowing dot of energy. The more Pixels that… Image Formation: Pixels & Color Spaces
“Professor Hoot,” Gizmo chirped, “how does this self-driving car see where it’s going?” Professor Hoot chuckled, his feathers ruffling. “Ah, that’s the magic of Computer Vision, my dear Gizmo! It’s how we teach machines to… Exploring Computer Vision & The Seeing Machine
The story of Kiko the overconfident student is a simple but accurate analogy for the concept of overfitting in machine learning and how cross-validation is used to prevent it. Here is a more technical breakdown… Overfitting, Cross validation: a story example of Kiko’s super secret
This typically means: Let’s go over a realistic and mockable example where: After that, we’ll go through an example where Then we’ll fix it by isolating the unsafe loss. After that, we’ll list which operations… Fixed: CUDA error: an illegal memory access was encountered
En-Ei-Et In Norwegian, the prefixes “ei-“, “en-“, and “et-” are used to indicate the grammatical gender of nouns. Here is how each is used: Note also that en mann (a man) & mannen (the man).… Norwegian vocabularies in cartoon
Lạc Long Quân, Âu Cơ & The Legend of the Hung Kings e story begins with Lạc Long Quân, a dragon lord, and Âu Cơ, a mountain fairy. Their union symbolizes the harmony between the… Vietnamese Most Interesting Fairy Tales – A collection
Hoán vị là một khái niệm quan trọng trong nhiều lĩnh vực sáng tạo, đặc biệt là âm nhạc và nghệ thuật. Nó liên quan đến việc thay đổi, sắp xếp lại các yếu tố… Hoán vị trong âm nhạc và nghệ thuật: Khám phá sáng tạo và sự biến đổi
Hiểu hành vi, sở thích và nhu cầu của khách hàng Hiểu hành vi, sở thích và nhu cầu của khách hàng là một phần quan trọng trong việc xây dựng chiến lược kinh doanh… Chiến Lược Hiểu Khách Hàng Bằng Dữ Liệu