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A Gentle Introduction to Symbolic AI
How can the latest AI solutions and applications benefit from symbolic AI? This article introduces and discusses this intriguing area of the field.
Published on: February 19, 2025 | Source:
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Math, Machine Learning & Coding Needed For LLMs
The goal of this article is to guide you through the essential mathematical foundations, machine learning techniques, and coding practices needed to work with LLMs.
Published on: February 19, 2025 | Source:How to Use the Trainer API in Hugging Face for Custom Training Loops
Learn how to develop custom training loop with Hugging Face Transformers and the Trainer API.
Published on: February 19, 2025 | Source:Data Scientist: From School to Work, Part I
Nowadays, data science projects do not end with the proof of concept; every project has the goal of being used in production. It is important, therefore, to deliver high-quality code. I have been working as a data scientist for more than ten years and I have noticed that juniors usually have a weak level in [β¦] The post Data Scientist: From School to Work, Part I appeared first on Towards Data Science.
Published on: February 19, 2025 | Source:Understanding Probability Distributions for Machine Learning with Python
In machine learning, probability distributions play a fundamental role for various reasons: modeling uncertainty of information and data, applying optimization processes with stochastic settings, and performing inference processes, to name a few.
Published on: February 19, 2025 | Source:How to Do Named Entity Recognition (NER) with a BERT Model
This post is in six parts; they are: β’ The Complexity of NER Systems β’ The Evolution of NER Technology β’ BERT's Revolutionary Approach to NER β’ Using DistilBERT with Hugging Face's Pipeline β’ Using DistilBERT Explicitly with AutoModelForTokenClassification β’ Best Practices for NER Implementation The challenge of Named Entity Recognition extends far beyond simple pattern matching or dictionary lookups.
Published on: February 19, 2025 | Source:How to Fine-Tune DistilBERT for Emotion Classification
The customer support teams were drowning with the overwhelming volume of customer inquiries at every company Iβve worked at. Have you had similar experiences? What if I told you that you could use AI to automatically identify, categorize, and even resolve the most common issues? By fine-tuning a transformer model like BERT, you can build [β¦] The post How to Fine-Tune DistilBERT for Emotion Classification appeared first...
Published on: February 19, 2025 | Source:Learning How to Play Atari Games Through Deep Neural Networks
In July 1959, Arthur Samuel developed one of the first agents to play the game of checkers. What constitutes an agent that plays checkers can be best described in Samuelβs own words, ββ¦a computer [that] can be programmed so that it will learn to play a better game of checkers than can be played by [β¦] The post Learning How to Play Atari Games Through Deep Neural Networks appeared first on Towards Data Science.
Published on: February 18, 2025 | Source:Honestly Uncertain
Ethical issues aside, should you be honest when asked how certain you are about some belief? Of course,it depends. In this blog post, youβll learn on what. A probabilistic quiz game David Spiegelhalterβs new (as of 2025) fantastic book, βThe Art of Uncertaintyβ β a must-read for everyone who deals with probabilities and their communication [β¦] The post Honestly Uncertain appeared first on Towards Data Science.
Published on: February 18, 2025 | Source:How LLMs Work: Pre-Training to Post-Training, Neural Networks, Hallucinations, and Inference
With the recent explosion of interest in large language models (LLMs), they often seem almost magical. But letβs demystify them. I wanted to step back and unpack the fundamentalsβbreaking down how LLMs are built, trained, and fine-tuned to become the AI systems we interact with today. This two-part deep dive is something Iβve been meaning [β¦] The post How LLMs Work: Pre-Training to Post-Training, Neural Networks,...
Published on: February 18, 2025 | Source:The Future of Data: How Decision Intelligence is Revolutionizing Data
In the past few years, technology and AI have evolved more than ever. As I read about the new concepts in tech and learn new skills and techniques each day, I feel in a state of limboβthere is so much content to consume and yet, very little content that I could create. In the rapidly [β¦] The post The Future of Data: How Decision Intelligence is Revolutionizing Data appeared first on Towards Data Science.
Published on: February 18, 2025 | Source:Retrieval Augmented Generation in SQLite
This is the second in a two-part series on using SQLite for machine learning. In my last article, I dove into how SQLite is rapidly becoming a production-ready database for web applications. In this article, I will discuss how to perform retrieval-augmented-generation using SQLite. If youβd like a custom web application with generative AI integration, [β¦] The post Retrieval Augmented Generation in SQLite appeared first...
Published on: February 18, 2025 | Source:7 MLOPs Projects for Beginners
Develop AI applications, test them, and deploy on the cloud using user-friendly MLOps tools and straightforward methods.
Published on: February 18, 2025 | Source:How Do I Improve My Logic Building in Programming?
In this article we will go through the tips and tricks that can help with your logic-building skills.
Published on: February 18, 2025 | Source:Understanding RAG Part V: Managing Context Length
Be sure to check out the previous articles in this series: β’
Published on: February 18, 2025 | Source:Become an AI Engineer for Free This Week
Learn AI for free on DataCamp from February 17 to 23.
Published on: February 17, 2025 | Source:Top 3 Video Generation Models
Generate high-quality videos in just a few minutes using these fast and accurate video generation models.
Published on: February 17, 2025 | Source:Tutorial: Semantic Clustering of User Messages with LLM Prompts
As a Developer Advocate, itβs challenging to keep up with user forum messages and understand the big picture of what users are saying. Thereβs plenty of valuable content β but how can you quickly spot the key conversations? In this tutorial, Iβll show you an AI hack to perform semantic clustering simply by prompting LLMs! [β¦] The post Tutorial: Semantic Clustering of User Messages with LLM Prompts appeared first on...
Published on: February 17, 2025 | Source:Parallelize NumPy Array Operations for Increased Speed
Enhance the array operational process with methods you may not have previously known.
Published on: February 17, 2025 | Source:On-Device Machine Learning in Spatial Computing
The landscape of computing is undergoing a profound transformation with the emergence of spatial computing platforms(VR and AR). As we step into this new era, the intersection of virtual reality, augmented reality, and on-device machine learning presents unprecedented opportunities for developers to create experiences that seamlessly blend digital content with the physical world. The introduction [β¦] The post On-Device...
Published on: February 17, 2025 | Source:Integrating TensorFlow and NumPy for Custom Operations
Combining the power of
Published on: February 17, 2025 | Source:How I Became A Machine Learning Engineer (No CS Degree, No Bootcamp)
Machine learning and AI are among the most popular topics nowadays, especially within the tech space. I am fortunate enough to work and develop with these technologies every day as a machine learning engineer! In this article, I will walk you through my journey to becoming a machine learning engineer, shedding some light and advice [β¦] The post How I Became A Machine Learning Engineer (No CS Degree, No Bootcamp)...
Published on: February 15, 2025 | Source:Roadmap to Becoming a Data Scientist, Part 4: Advanced Machine Learning
Introduction Data science is undoubtedly one of the most fascinating fields today.Following significant breakthroughs in machine learning about a decade ago, data science has surged in popularity within the tech community.Each year, we witness increasingly powerful tools that once seemed unimaginable.Innovations such as theTransformer architecture,ChatGPT, theRetrieval-Augmented Generation (RAG) framework, and...
Published on: February 14, 2025 | Source:Publish Interactive Data Visualizations for Free with Python and Marimo
Working in data science, it can be hard to share insights from complex datasets using only static figures. All the facets that describe the shape and meaning of interesting data are not always captured in a handful of pre-generated figures. While we have powerful technologies available for presenting interactive figuresβwhere a viewer can rotate, filter, [β¦] The post Publish Interactive Data Visualizations for Free...
Published on: February 14, 2025 | Source:5 Tips for Building a Data Science Portfolio
Not every data science portfolio is worth showcasing. Follow these five tips to build a portfolio that impresses employers and gets you a job.
Published on: February 14, 2025 | Source:Building a Data Engineering Center of Excellence
As data continues to grow in importance and become more complex, the need for skilled data engineers has never been greater. But what is data engineering, and why is it so important? In this blog post, we will discuss the essential components of a functioning data engineering practice and why data engineering is becoming increasingly [β¦] The post Building a Data Engineering Center of Excellence appeared first on...
Published on: February 14, 2025 | Source:Learnings from a Machine Learning Engineer β Part 5: The Training
In this fifth part of my series, I will outline the steps for creating a Docker container for training your image classification model, evaluating performance, and preparing for deployment. AI/ML engineers would prefer to focus on model training and data engineering, but the reality is that we also need to understand the infrastructure and mechanics [β¦] The post Learnings from a Machine Learning Engineer β Part 5: The...
Published on: February 13, 2025 | Source:Learnings from a Machine Learning Engineer β Part 3: The Evaluation
In this third part of my series, I will explore the evaluation process which is a critical piece that will lead to a cleaner data set and elevate your model performance. We will see the difference between evaluation of atrainedmodel (one not yet in production), and evaluation of adeployedmodel (one making real-world predictions). InPart 1, [β¦] The post Learnings from a Machine Learning Engineer β Part 3: The Evaluation...
Published on: February 13, 2025 | Source:Learnings from a Machine Learning Engineer β Part 1: The Data
It is said that in order for a machine learning model to be successful, you need to have good data. While this is true (and pretty much obvious), it is extremely difficult to define, build, and sustain good data. Let me share with you the unique processes that I have learned over several years building [β¦] The post Learnings from a Machine Learning Engineer β Part 1: The Data appeared first on Towards Data Science.
Published on: February 13, 2025 | Source:Learnings from a Machine Learning Engineer β Part 4: The Model
In this latest part of my series, I will share what I have learned on selecting a model for image classification and how to fine tune that model. I will also show how you can leverage the model to accelerate your labelling process, and finally how to justify your efforts by generating usage and performance [β¦] The post Learnings from a Machine Learning Engineer β Part 4: The Model appeared first on Towards Data...
Published on: February 13, 2025 | Source:Learnings from a Machine Learning Engineer β Part 2: The Data Sets
InPart 1, we discussed the importance of collecting good image data and assigning proper labels for your image classification project to be successful. Also, we talked about classes and sub-classes of your data. These may seem pretty straight forward concepts, but itβs important to have a solid understanding going forward. So, if you havenβt, please [β¦] The post Learnings from a Machine Learning Engineer β Part 2: The...
Published on: February 13, 2025 | Source:Bridging the Gap: Democratizing AI for All
Letβs explore how democratizing AI can level the playing field and create opportunities for all, no matter the background or resources.
Published on: February 13, 2025 | Source:How to Scale Sklearn with Dask
Here's how Dask applies the building blocks of sklearn to bring ML modeling workflows to the next level of scalability via high-performance parallel computing
Published on: February 13, 2025 | Source:Prompt Engineering Patterns for Successful RAG Implementations
You know it as well as I do: people are relying more and more on generative AI and large language models (LLM) for quick and easy information acquisition.
Published on: February 13, 2025 | Source:Should Data Scientists Care About Quantum Computing?
I am sure the quantum hype has reached every person in tech (and outside it, most probably). With some over-the-top claims, like βsome company has proved quantum supremacy,β βthe quantum revolution is here,β or my favorite, βquantum computers are here, and it will make classical computers obsolete.β I am going to be honest with you; [β¦] The post Should Data Scientists Care About Quantum Computing? appeared first on...
Published on: February 13, 2025 | Source: