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    Artificial Intelligence

    Core Machine Learning Skills, Revisited

    ProfitlyAIBy ProfitlyAIJune 25, 2025No Comments3 Mins Read
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    By no means miss a brand new version of The Variable, our weekly publication that includes a top-notch choice of editors’ picks, deep dives, neighborhood information, and extra.

    With all the thrill round brokers, LLMs, and the instruments they energy, it’s typically simple (or a minimum of tempting) to suppose that basic machine studying workflows—characteristic choice, mannequin monitoring, and the like—will quickly develop into out of date.

    The articles we chosen for you this week paint a unique and extra nuanced image. Positive, practitioners have highly effective new toys to play with, however the inherent worth in understanding how fashions work (and break) isn’t going wherever. Learn on to be taught how one can proceed to develop as a knowledge or ML skilled within the “AI is in every single place!” age.


    I Received $10,000 in a Machine Studying Competitors — Right here’s My Full Technique

    Strolling us by the method she adopted to excel at a current competitors, Claudia Ng highlights how “success in machine studying isn’t about having the fanciest instruments or essentially the most advanced algorithms,” however relatively all about “understanding your downside, making use of strong fundamentals, and specializing in what really strikes the needle.”

    Grad-CAM from Scratch with PyTorch Hooks

    In a brand new hands-on tutorial, Conor O’Sullivan zooms in on a robust explainable-AI approach for convolutional neural networks.

    Knowledge Drift Is Not the Precise Drawback: Your Monitoring Technique Is

    “I feel the true concern is that the majority organizations monitor information with out understanding it.” Mahe Jabeen Abdul explains why it’s so difficult to know what to observe.

    Measure Actual Mannequin Accuracy When Labels Are Noisy

    Leveraging Bayesian strategies and Python, Erdogan Taskesen’s deep dive focuses on successfully figuring out causality throughout variables.


    This Week’s Should-Learn Tales

    Make amends for the articles our neighborhood has been buzzing about in current days. Right here’s a roundup of this week’s trending tales:

    Mannequin Context Protocol (MCP) Tutorial: Construct Your First MCP Server in 6 Steps, by Destin Gong

    Cell App Growth with Python, by Mauro Di Pietro

    Design Smarter Prompts and Increase Your LLM Output: Actual Methods from an AI Engineer’s Toolbox, by Ugo Pradère


    Different Really useful Reads

    Why not department out into another fascinating areas within the huge world of information, ML, and AI?


    Meet Our New Authors

    Discover top-notch work from a few of our just lately added contributors:

    • Sourav Mohile, a Mumbai-based information scientist, shared a complete information to regularization.
    • Hugo Ducruc‘s debut article presents a thought-provoking reflection on the strides AI has made in recent times.
    • Moulik Gupta unpacks the progressive reminiscence perform within the just lately unveiled Titans structure.

    We love publishing articles from new authors, so should you’ve just lately written an attention-grabbing venture walkthrough, tutorial, or theoretical reflection on any of our core subjects, why not share it with us?


    Subscribe to Our Publication



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