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Axon

@axonlearn.app

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Because normal Data and AI apps are boring
Learn ML with Axon👇
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Start small: label examples, try a prediction, then check your answer. Interactive practice gives you something concrete to learn from. Comment "ML" for the link. #datascience #learntocode #machinelearning by @axonlearn.app
For a classification model, inspect the confusion matrix, precision, and recall alongside accuracy. Identify the cost of false positives and false negatives for your question. Choose a metric that fits the task. The scikit-learn Metrics and scoring reference explains the available measures; regression needs different metrics. Resource: scikit-learn — Metrics and scoring https://scikit-learn.org/stable/modules/model_evaluation.html Save this for your next practice session. #learntocode #datascience #machinelearning by @axonlearn.app
Three ideas for a portfolio refresh: 1. NBA Shot Quality Model — investigate what makes a shot difficult. 2. World Cup Goal Predictor — explore match data with XGBoost. 3. Spotify Hit Predictor — test how audio features relate to popularity. Show your question, your baseline, and what the result does not tell you. Comment "projects" for the link. #datascience #learntocode #machinelearning by @axonlearn.app
Before trusting a score, check for data leakage. Split the data before learning preprocessing parameters. Fit scalers or feature selection on training data only, then apply the learned transformation to evaluation data. The scikit-learn Common pitfalls guide shows examples and how pipelines help keep these steps together. Resource: scikit-learn — Common pitfalls https://scikit-learn.org/stable/common_pitfalls.html Save this for your next practice session. #learntocode #datascience #machinelearning by @axonlearn.app
A path toward machine learning engineering: Python, Git, machine learning, deep learning, then MLOps. Practice each stage and take a model beyond the notebook. Comment "ML" for the link. #datascience #learntocode #machinelearning by @axonlearn.app
The scikit-learn Getting Started guide introduces fitting, prediction, preprocessing, pipelines, and evaluation. Pick a small documented example and build a baseline. Keep evaluation data separate. Explain what the model is predicting and which metric you are checking before adding complexity. Resource: scikit-learn — Getting Started https://scikit-learn.org/stable/getting_started.html Save this for your next practice session. #learntocode #datascience #machinelearning by @axonlearn.app
3 machine learning projects to build next: 1. Spotify Hit Predictor — explore audio features and classification. 2. Chess Move Evaluator — learn how a value network scores positions. 3. NFL Predictor Model — compare models and watch for data leakage. Choose one, build a baseline, and explain its limitations. Comment "Projects" for the link. #datascience #learntocode #machinelearning by @axonlearn.app
Pro Git is available to read online at git-scm.com. Start with Git Basics: recording changes and viewing commit history. In a practice repository, change one file, inspect git diff, then stage and commit it. Look at the history so you can connect each command to what actually changed. Resource: Pro Git — Online book https://git-scm.com/book/en/v2 Save this for your next practice session. #learntocode #datascience #machinelearning by @axonlearn.app
You can start learning before you feel ready. 🎮 Try a short game, make a choice, and see what happens. That’s one way to begin exploring machine learning. Comment “Learn” and I’ll send you the Axon Learn link! #machinelearning #datascience #coding #learntocode by @axonlearn.app
Choose fields, build a chart, and see what changes. A practical way to start exploring Power BI. Comment "Learn" for the link. #datascience #learntocode #machinelearning by @axonlearn.app
The Matplotlib pyplot tutorial is a practical reference for basic plots, labels, and styling. Plot a small series and label the axes with units. Write one sentence describing the question the chart answers. Keep the labels clear before spending time on colors. Resource: Matplotlib — Pyplot tutorial https://matplotlib.org/stable/tutorials/pyplot.html Save this for your next practice session. #learntocode #datascience #machinelearning by @axonlearn.app
A different way to start learning machine learning 🎮 Small games. A few decisions. A chance to see what clicks. Comment “Learn” and I’ll send you the Axon Learn link! #machinelearning #codingisfun #learntocode #cs by @axonlearn.app

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