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#General #Development #Mobile Development #Cloud & DevOps #Cybersecurity & Privacy #AI & Data Science #Hardware & Gadgets #Design & UXTop 5 Tips for Fine-Tuning LLMs
Whether youβre building an LLM from scratch or augmenting an LLM with additional finetuning data, following these tips will deliver a more robust model.
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Combining Large and Small LLMs to Boost Inference Time and Quality
Implementing Speculative and Contrastive DecodingLarge Language models are comprised of billions of parameters (weights). For each word it generates, the model has to perform computationally expensive calculations across all of these parameters.Large Language models accept a sentence, or sequence of tokens, and generate a probability distribution of the next most likelytoken.Thus, typically decoding n tokens (or...
How to Integrate AI and Data Science into Your Business Strategy
DATA SCIENCE CONSULTINGInsider consulting guide to conducting a successful 2-day executive workshopImage by author usingCanvaβOur industry does not respect traditionβit only respects innovation.ββSatya Nadella, CEO Microsoft, Letter to employees in2014While not all industries are as competitive and cutthroat as the software and cloud industries, innovating and applying the latest technological developments is a...
NumPy for Simulating Random Processes and Monte Carlo Methods
Learn how to use NumPy for robust computational simulation.
Reinforcement Learning: Self-Driving Cars to Self-Driving Labs
Understanding AI applications in bio for machine learning engineersPhoto by Ousa Chea onUnsplashAnyone who has tried teaching a dog new tricks knows the basics of reinforcement learning. We can modify the dogβs behavior by repeatedly offering rewards for obedience and punishments for misbehavior. In reinforcement learning (RL), the dog would be an agent, exploring its environment and receiving rewards or penalties...
Play the 20 Questions Game Against an LLM
And learn about LLM architecture techniques, parsed output, test design and performance measurement of your systemContinue reading on Towards Data Science Β»
5 Outside the Box Applications of Natural Language Processing
The NLP applications you might never know existed.
5 Python One-Liners to Kick Off Your Data Exploration
How to kickstart your EDA using simple one linersContinue reading on Towards Data Science Β»
Lasso and Elastic Net Regressions, Explained: A Visual Guide with Code Examples
REGRESSION ALGORITHMRoping in key features with coordinate descentLeast Squares Regression, Explained: A Visual Guide with Code Examples for BeginnersLinear regression comes in different types: Least Squares methods form the foundation, from the classic Ordinary Least Squares (OLS) to Ridge regression with its regularization to prevent overfitting. Then thereβs Lasso regression, which takes a unique approach by...
Bridging the Data Literacy Gap
The Advent, Evolution, and Current state of βData TranslatorsβIntroductionWith Data being constantly glorified as the most valuable asset organizations can own, leaders and decision-makers are always looking for effective ways to put their data insights to use. Every time customers interact with digital products, millions of data points are generated and the opportunity loss of not harnessing these data points to make...
Multimodal RAG: Process Any File Type with AI
A beginner-friendly guide with example (Python)codeThis is the third article in a larger series on multimodal AI. In the previous posts, we discussed multimodal LLMs and embedding models, respectively. In this article, we will combine these ideas to enable the development of multimodal RAG systems. Iβll start by reviewing key concepts and then share example code for implementing such asystem.Image fromCanva.Language...
Chat with Your Images using Multimodal LLMs
Chat with Your Images Using Llama 3.2-Vision Multimodal LLMsLearn how to build Llama 3.2-Vision locally in a chat-like mode, and explore its Multimodal skills on a ColabnotebookAnnotated image by author. Original image byPixabay.IntroductionThe integration of vision capabilities with Large Language Models (LLMs) is revolutionizing the computer vision field through multimodal LLMs (MLLM). These models combine text and...
Who Does What in Data? A Practical Introduction to the Role of a Data Engineer & Data Scientist
What does a data engineer do differently to a data scientist?Continue reading on Towards Data Science Β»
GPS Interpolation Using Maps and Kinematics
How do you apply dead reckoning to your geospatial dataset?The picture above illustrates the GPS interpolation process. The red dots represent the known and repeated GPS locations, with more than one location per dot, while the blue dots represent the inferred locations of the repeated points along the road using the vehicleβs speed. (Image created by the author using OpenStreetMap data and imagery.)Modern cars, vans,...
Building a Fantasy Football Research Agent with LangGraph
An end-to-end guide covering integration with the Sleeper API, creation of a Streamlit UI, and deployment via AWSCDKPhoto by Dmitriy Demidov onUnsplashItβs embarrassing how much time I spend thinking about my fantasy footballteam.Managing a squad means processing a firehose of informationβinjury reports, expert projections, upcoming bye weeks, and favorable matchups. And itβs not just the volume of data, but the...
From Code to Paper: Using GPT Models and Python to Generate Scientific LaTeX Documents
Automating scientific code documentation: a GPT-powered POC for streamlined workflows.Illustration picture. Generated byChatGPT.IntroductionWorking on scientific papers often involves translating algorithms into scientific formulas, typically formatted in LaTeX. This process can be tedious and time-consuming, especially in large projects, as it requires constant back-and-forth between the code repository and the LaTeX...
DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Languageβ¦
DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large LanguageModelsTraditional RAG vs. dynamicRAGIn this article, I explore the fundamental concepts explained in the research paper titled βDRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Modelsβ by Weihang Su, Yichen Tang, Qingyao Ai, Zhijing Wu, and Yiqun Liu. This paper can be accessed...
Google DeepMind at NeurIPS 2024
Advancing adaptive AI agents, empowering 3D scene creation, and innovating LLM training for a smarter, safer future
How to Install and Run LLMs Locally on Android Phones
Learn how to bring the power of AI right to your Android phoneβno cloud, no internet, just pure on-device intelligence!
How to Transition Into Data Science-and Within Data Science
How to Transition Into Data Scienceβand Within DataScienceFeeling inspired to write your first TDS post? Weβre always open to contributions from newauthors.With January just around the corner, weβre about to enter prime career-moves season: that exciting time of the year when many data and machine learning professionals assess their career growth and explore new opportunities, and newcomers to the field plan the next...
From Novice to Pro: A Roadmap for Your Machine Learning Career
Let's take a look at a concise roadmap to building a lasting and effective machine learning career.
Donβt Flood Your Algorithms With Easy ExamplesβββIt Costs Money
A common mistake that slows down training and burns cashContinue reading on Towards Data Science Β»
Break Free from the IC Mindset. You Are a Manager Now.
5 mistakes I see new managers make in their transition into leadership rolesContinue reading on Towards Data Science Β»
5 Beginner-Friendly Projects to Learn LLMs & RAG
I believe in the 'learning by doing' approachβyou learn more this way.
How to Interpret Matrix ExpressionsβββTransformations
Matrix algebra for a data scientistPhoto by Ben Allan onUnsplashThis article begins a series for anyone who finds matrix algebra overwhelming. My goal is to turn what youβre afraid of into what youβre fascinated by. Youβll find it especially helpful if you want to understand machine learning concepts andmethods.Table of contents:IntroductionPrerequisitesMatrix-vector multiplicationTranspositionComposition of...
What Teaching AI Taught me About Data Skills & People
Three key lessons from my journey as a corporate AIeducatorPhoto by MikhailNilov.As an AI Educator, my job was to equip corporate teams with the data & AI skills they needed to thrive. But looking back, I realized that I learned far more from them that they did fromme.Hereβs what teaching 2000+ employees at 10+ large enterprises taught me about data skills, people, and the art of learning.1. Data Science has More...
Introducing Univariate Exemplar Recommenders: how to profile Customer Behavior in a single vector
Customer ProfilingSurveying and improving the current methodologies for customer profiling***To understand this article, knowledge of embeddings, clustering, and recommendation systems is required. The implementation of this algorithm has been released on GitHub and is fully open-source. I am open to criticism and welcome any feedback.Most platforms, nowadays, understand that tailoring individual choices for each...
Step-by-Step Guide for Building Bump Charts in Plotly
Learn how to create custom bump charts in Python using Plotly for data visualizationContinue reading on Towards Data Science Β»
7 Projects to Master Data Engineering
Learn to build, run, and manage data engineering pipelines both locally and in the cloud using popular tools.
An Introduction to CTEs in SQL
Explore how Common Table Expression (CTE) can help optimize SQL performance and readabilityContinue reading on Towards Data Science Β»
GenCast predicts weather and the risks of extreme conditions with state-of-the-art accuracy
New AI model advances the prediction of weather uncertainties and risks, delivering faster, more accurate forecasts up to 15 days ahead
Machine Learning Basics I Look for in Data Scientist Interviews
Letβs build our breadth of science together.Continue reading on Towards Data Science Β»
Getting Started with MongoDB: Installation and Setup Guide
MongoDB is a database thatβs great for handling large amounts of diverse data. This article walks you through installing MongoDB and using the MongoDB Shell to manage your data easily.
Genie 2: A large-scale foundation world model
Generating unlimited diverse training environments for future general agents
SQL vs. Calculators: Building Champion/Challenger Tests from Scratch
CODE OR CLICK: WHAT IS BETTER FOR A/BTESTINGIn depth SQL code for creating your own statistical testdesignImage from Imagen3The $300 Million Button: How A/B Testing Changed E-Commerce ForeverI am sure a lot of people are aware of the $300 million button story. For those that are not aware of the story, it is about a major e-commerce platform losing millions in potential revenue due to customer drop-offs at checkout....