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My Top Picks: 5 Free NLP Courses Iβd Recommend for 2025
Want to become an NLP pro by 2025? Check out these top free courses and learn from experts whoβve shaped the future of language models.
Published on: January 16, 2025 | Source:
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The Death of Human-Written Code Tutorials in the ChatGPT EraΒ β¦ Or Not?
An argument in favor of human-written coding tutorials in the new age of LLMs.Continue reading on Towards Data Science Β»
Published on: January 16, 2025 | Source:Learnings from a Machine Learning EngineerβββPart 1: The Data
Practical insights for a data-driven approach to model optimizationContinue reading on Towards Data Science Β»
Published on: January 15, 2025 | Source:Water Cooler Small Talk: Benfordβs Law
A look into the strange first digit distribution of naturally occurring datasetsContinue reading on Towards Data Science Β»
Published on: January 15, 2025 | Source:Qubits Explained: Everything You Need to Know
A deep dive into the building block of quantum computers.Continue reading on Towards Data Science Β»
Published on: January 15, 2025 | Source:Understanding Flash Attention: Writing the Algorithm from Scratch in Triton
Find out how Flash Attention works. Afterward, weβll refine our understanding by writing a GPU kernel of the algorithm in Triton.Continue reading on Towards Data Science Β»
Published on: January 15, 2025 | Source:A Gentle Introduction to Rust for Python Programmers
Rust is a systems programming language that offers high performance and safety. Python programmers will find Rust's syntax familiar but with more control over memory and performance.
Published on: January 15, 2025 | Source:Unlocking the Power of Machine Learning in Analytics: Practical Use Cases and Skills
Your essential machine learning checklist to excel as a data scientist in analyticsContinue reading on Towards Data Science Β»
Published on: January 15, 2025 | Source:Recursive Walks down User Referral Trees
Recursive Walks Down User ReferralTreesMeasuring the total influence of users in a user referral program by traversing indirect referralsWithin many modern software products, there is a chance for users to refer/promote the application to other users. A natural question to ask with these referral programs is: βwho is our most influential user promoter of the product?β One naive way to answer this question is to simply...
Published on: January 15, 2025 | Source:Answer Data Questions for Non-Technical Stakeholders
In this article, I will go through key elements that will help you answer data questions for your non-technical audience with ease.
Published on: January 15, 2025 | Source:LossVal Explained: Efficiently Estimate the Importance of Your Training Data
LossVal Explained: Efficient Data Valuation for NeuralNetworksHow to exploit the loss function to efficiently estimate the importance of your trainingdataData Valuation visualized. Understanding how important each training sample is for the performance of your machine learning model. (Image byauthor.)This blog post summarizes and explains our paper βLossVal: Efficient Data Valuation for Neural Networksβ.Not all data is...
Published on: January 15, 2025 | Source:LLM Routingβββthe Heart of Any Practical AI Chatbot Application
How to building reliable, scalable and robust AI applicationsβ explained in five minutes.Continue reading on Towards Data Science Β»
Published on: January 15, 2025 | Source:Exploring Multilingual LLMs with Aya Expanse
Read this to understand the most advanced open source multilingual model.
Published on: January 15, 2025 | Source:Scaling Segmentation with Blender: How to Automate Dataset Creation
A Step-by-Step Guide to Generating Synthetic Data for Training AIModelsPhoto by Lina Trochez onUnsplashIf you have ever trained a segmentation model for a new project, you probably know itβs not about the model. Itβs about thedata.Collecting images is often straightforward; you can usually find plenty on platforms like Unsplash, or even use Generative AI tools such as Stable Diffusion to generatemore:How to Train an...
Published on: January 15, 2025 | Source:Visualizing XGBoost Parameters: A Data Scientistβs Guide To Better Models
Why understanding parameters is critical to building robust modelsContinue reading on Towards Data Science Β»
Published on: January 15, 2025 | Source:Hands-On Delivery Routes Optimization (TSP) with AI, Using LKH and Python
Hereβs how to optimize the delivery routes, from theory to code.Continue reading on Towards Data Science Β»
Published on: January 14, 2025 | Source:How To: Forecast Time Series Using Lags
Lag columns can significantly boost your modelβs performanceContinue reading on Towards Data Science Β»
Published on: January 14, 2025 | Source:Static and Dynamic Attention: Implications for Graph Neural Networks
Examining the expressive capacity of Graph Attention NetworksImage by theauthorIn graph representation learning, neighborhood aggregation is one of the most well-studied and investigated areas, among which attention-based methods largely remain state-of-the-art. Leveraging learnable attention scores for weighted aggregations, graph attention networks exhibit higher expressivity than naive aggregation schemes. In graph...
Published on: January 14, 2025 | Source:Deep Dive into KV-Caching In Mistral
Ever wondered why the time to first token in LLMs is high but subsequent tokens are superfast?In this post, I dive into the details of KV-Caching used in Mistral, a topic I initially found quite daunting. However, as I delved deeper, it became a fascinating subject, especially when it explained why the time to first token (TTFT) in these language models is generally highβa pattern I noticed during countless API calls.I...
Published on: January 14, 2025 | Source:Scale Experiment Decision-Making with Programmatic Decision Rules
Decide what to do with experiment results incodePhoto by Cytonn Photography onUnsplashThe experiment lifecycle is like the human lifecycle. First, a person or idea is born, then it develops, then it is tested, then its test ends, and then the Gods (or Product Managers) decide itsworth.But a lot of things happen during a life or an experiment. Sometimes, a person or idea is good in one way but bad in another. How are...
Published on: January 14, 2025 | Source:The Complete Introduction to Time Series Classification in Python
Learn the fundamental concepts of time series classification and apply them in a small project using PythonContinue reading on Towards Data Science Β»
Published on: January 14, 2025 | Source:Why Normalization Is Crucial for Policy Evaluation in Reinforcement Learning
Enhancing Accuracy in Reinforcement Learning Policy Evaluation through NormalizationContinue reading on Towards Data Science Β»
Published on: January 14, 2025 | Source:Build Your First API with Python and AWS
Learn how to create a simple, yet powerful REST API with FastAPI, DynamoDB, and AWS Lambda Functions.Continue reading on Towards Data Science Β»
Published on: January 14, 2025 | Source:These Are The Soft Skills You Will Need As A Data Scientist in 2025
Check these top recommendations on the soft skills you need to refine and perfect for 2025.
Published on: January 14, 2025 | Source:Awesome Plotly with code series (Part 8): How to balance dominant bar chart categories
Discover the #1 strategy to handle skyscraper bars in your chartsContinue reading on Towards Data Science Β»
Published on: January 14, 2025 | Source:10 Essential SQL Commands for Data Analysis
What are essential commands for data analysis in SQL? This article will answer this question by mentioning 10 SQL commands.
Published on: January 14, 2025 | Source:7 Easy Ways to Make Passive Income with Large Language Models
Looking for extra income? Here are 7 creative ways to use large language models for passive earnings!
Published on: January 14, 2025 | Source:Four Ways to Improve Statistical Power in A/B Testing (Without Increasing Test Duration, Duh)
In A/B testing, you often have to balance statistical power and how long the test takes. Learn how Allocation, Effect Size, CUPED & Binarization can helpyou.Image byauthorIn A/B testing, you often have to balance statistical power and how long the test takes. You want a strong test that can find any effects, which usually means you need a lot of users. This makes the test longer to get enough statistical power....
Published on: January 13, 2025 | Source:The AI (R)Evolution, Looking From 2024 Into the Immediate Future
Witnessing rapid innovation, fierce competition, and transformative tools for life, work, and human developmentContinue reading on Towards Data Science Β»
Published on: January 13, 2025 | Source:Contextual Topic Modelling in Chinese Corpora with KeyNMF
A comprehensive guide on getting the most out of your Chinese topic models, from preprocessing to interpretation.With our recent paper on discourse dynamics in European Chinese diaspora media, our team has tapped into an almost unanimous frustration with the quality of topic modelling approaches when applied to Chinese data. In this article, I will introduce you to our novel topic modelling method, KeyNMF, and how to...
Published on: January 13, 2025 | Source:llama.cpp: Writing A Simple C++ Inference Program for GGUF LLM Models
Exploring llama.cpp internals and a basic chat programflowPhoto by Mathew Schwartz onUnsplashllama.cpp has revolutionized the space of LLM inference by the means of wide adoption and simplicity. It has enabled enterprises and individual developers to deploy LLMs on devices ranging from SBCs to multi-GPU clusters. Though working with llama.cpp has been made easy by its language bindings, working in C/C++ might be a...
Published on: January 13, 2025 | Source:A Multimodal AI Assistant: Combining Local and Cloud Models
Dalle-3βs interpretation of βa quirky robot wearing a tool belt and puzzling over questionβ. Image generated by theauthor.Use LangGraph, mlx and Florence2 to build an agent that answers complex image questions, with the option to run everything locally.In this article weβll use LangGraph in conjunction with several specialized models to build a rudimentary agent that can answer complex questions about an image,...
Published on: January 13, 2025 | Source:Going Beyond Bias-Variance Tradeoff Into Double Descent Phenomenon
Itβs not how many times you get knocked down that count, itβs how many times you get back up.Continue reading on Towards Data Science Β»
Published on: January 13, 2025 | Source:IT Strategies: Built to Last
Why Reevaluating Our Core Assumptions About Data and Integration Creates Significant ValueContinue reading on Towards Data Science Β»
Published on: January 13, 2025 | Source:Building Deterministic GenAI Chatbots In Regulated Industries
How to Build Reliable and Contextual AI Chatbots for Finance, Healthcare and Other IndustriesContinue reading on Towards Data Science Β»
Published on: January 13, 2025 | Source: