Posts with #MLProject

#MLProject

Public posts on X that use #MLProject.

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  1. Aditya Mishra@AdiMishra_akm
    @AdiMishra_akm
    Technical Highlights: • ML Pipeline using ColumnTransformer • One-hot encoding + scaling • Feature importance extraction • Model serialization with Joblib • Real-time prediction via Streamlit Focused on production-style structure, not just model accuracy. #Python #MLProject
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  2. Omkar Kashid@Omkar_Kashid_
    PROJECT LAUNCH!🚀 I built and deployed an end-to-end Crop Recommendation System using ML! -> This is a basic ML Project From Jupyter Notebook to a live Streamlit app. Check it out:👉 #MLProject #DataScience #Streamlit #AgTech Feedback welcome!👇
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  3. Arihant Jain@arihant105
    Built an End-to-End ML project, Spam-Message-Detector The source code with Dockerfile is available here: #MLproject
    Download
    10169
  4. FocusUs@FocusUs2
    HDPS Thread : Heart Disease Prediction System (HDPS) is simple, userfriendly web-based application that can predict heart disease using Machine Learning Algorithm Logistic Regression. 13 different attributes like age, sex, cholesterol, etc. are taken from the User to predict HD.
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  5. ジャマコ🍛@msjamako
    演奏会は、企画進行運営スタッフが盤石だと、演奏者は集中できてよりよい演奏になり、聴く側も幸せになるものと実感。そして、三者ともお互いに感謝してるからこそ、演奏会は大成功するものと、実感しました。昨日の中島裕康さんの箏リサイタル@近江楽堂 #mlproject #中島裕康 #箏 #近江楽堂
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  6. Anne Ramsay@ramsaybaa
    🐑The final data collection for the Merino Lifetime Productivity project wrapped up in August 2024! Nearly 10 years & 2,000,070 data points collected. Full analysis is now underway! Stay tuned for insights 🔍 #merino #SheepBreeding #MLProject
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  7. Anne Ramsay@ramsaybaa
    We are off and running at the #MLProject Pingelly field day. @bron_clarke running us thru impact of classing on performance. Also looking at change in FBV over time, early FBV were reasonable at selecting lifetime wool performance. Repro results suggest need repeat records.
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    119
  8. neptune.ai@neptune_ai
    Choosing proper classification metrics is a crucial yet difficult part of every #MLProject. How to select one that works for your problem best? 👉 Continue reading to understand the key trade-offs that will help you make metric-related decisions easier:
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  9. Uruit@UruIT
    Here’s a list, created by Marcelo Lopez, co-founder and CEO of UruIT, of the best #MachineLearning platforms, with their respective pricing and benefits, so you can choose which one works best for your #MLproject!
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