#30daysofML - Twitter Hashtag

4 months ago

Day 14 of 30 Days of ML 📊 Today I explored Cross-Validation understanding why a single train-test split isn’t enough. It gives a more reliable estimate of performance and helps detect overfitting early. #30DaysOfML

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Sudhanshu Gochar @GocharSudhanshu

4 months ago

📅 Day 17/30 – ML (Deep Learning) journey 💪 🚀 Built a Resume Category Prediction system using NLP + Perceptron (TF-IDF) 👉 GitHub: https://t.co/2diq0Sg22Q #MachineLearning #DeepLearning #DataScience #30DaysOfML #LearningInPublic #AI

GocharSudhanshu's tweet photo. 📅 Day 17/30 – ML (Deep Learning) journey 💪

🚀 Built a Resume Category Prediction system using NLP + Perceptron (TF-IDF)

👉 GitHub:
https://t.co/2diq0Sg22Q
#MachineLearning #DeepLearning #DataScience #30DaysOfML #LearningInPublic #AI https://t.co/Ezd5qcQThR

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kap10.ai @Kap10__

7 months ago

Starting my #30DaysOfML journey today! Daily ML (no excuses) - focusing on mastering the fundamentals. For the next 30 days, I’ll be posting my progress publicly. If you’re learning ML too, drop a “+1” and let’s grow together. Consistency > Perfection 🚀 #30DaysOfML #Python

Kap10__'s tweet photo. Starting my #30DaysOfML journey today!

Daily ML (no excuses) - focusing on mastering the fundamentals.

For the next 30 days, I’ll be posting my progress publicly.
If you’re learning ML too, drop a “+1” and let’s grow together.

Consistency > Perfection 🚀

#30DaysOfML #Python https://t.co/pThtBuqAgf

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Neural @imNeural

9 months ago

Day 13 of #30DaysOfML > Solved "Compute the Cross Product of Two 3D Vectors" problem today. > Approach: -> Manual: check dims, unpack & apply formula -> NumPy: np.cross(a,b) + convert back to list From formula to function in just a few lines, that’s the magic💯 @real_deep_ml

imNeural's tweet photo. Day 13 of #30DaysOfML

> Solved "Compute the Cross Product of Two 3D Vectors" problem today.
> Approach:
-> Manual: check dims, unpack & apply formula
-> NumPy: np.cross(a,b) + convert back to list

From formula to function in just a few lines, that’s the magic💯
@real_deep_ml https://t.co/xT5lbxMRMn

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Piyush Aggarwal @Piyush_tech2024

10 months ago

Day 2 of #30DaysOfML ✅ Today I explored how to handle missing values in ML: 1️⃣ Imputation (filling missing data) 2️⃣ Dropping (removing incomplete rows/columns) Also revised the basics of Pandas & NumPy 📊 Step by step, getting stronger! 💪 #AI #ML #100DaysOfCode

Piyush_tech2024's tweet photo. Day 2 of #30DaysOfML ✅

Today I explored how to handle missing values in ML:
1️⃣ Imputation (filling missing data)
2️⃣ Dropping (removing incomplete rows/columns)

Also revised the basics of Pandas & NumPy 📊
Step by step, getting stronger! 💪
#AI #ML #100DaysOfCode https://t.co/gpbKVu1uBt

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Piyush Aggarwal @Piyush_tech2024

10 months ago

Starting my 30 Days of ML journey today! 🚀 Day 1: Learned how to collect datasets for ML projects. 📊 Some great sources: 1️⃣ Kaggle 2️⃣ Google Datasets 3️⃣ UCI Machine Learning Repository Super excited to explore more in ML 🤖 #30DaysOfML #AI #ML #100DaysOfCode

Piyush_tech2024's tweet photo. Starting my 30 Days of ML journey today! 🚀

Day 1: Learned how to collect datasets for ML projects. 📊
Some great sources:
1️⃣ Kaggle
2️⃣ Google Datasets
3️⃣ UCI Machine Learning Repository

Super excited to explore more in ML 🤖
#30DaysOfML #AI #ML #100DaysOfCode https://t.co/3bufeQzKCE

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Ife Abdulsamad | Organizing #careerfest26 @Ife_abdulsamad

10 months ago

Up next, moving from theory to hands-on ML! (Building ML Models)🚀 Let's go🚀🚀 #30DaysOfML

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Ife Abdulsamad | Organizing #careerfest26 @Ife_abdulsamad

10 months ago

🧵 Day 3/30 – Algorithms in Machine Learning #30DaysOfML Machine Learning (ML) algorithms are the backbone of how models learn from data. They can be grouped based on the type of learning approach used. Let's break it down 👇

Ife_abdulsamad's tweet photo. 🧵 Day 3/30 – Algorithms in Machine Learning
#30DaysOfML
Machine Learning (ML) algorithms are the backbone of how models learn from data.
They can be grouped based on the type of learning approach used.
Let's break it down 👇 https://t.co/8nWmfiTyDe

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Ife Abdulsamad | Organizing #careerfest26 @Ife_abdulsamad

10 months ago

Day 2 – Types of Machine Learning 🤖 ML can be grouped into 3 main types: Supervised Learning Unsupervised Learning Reinforcement Learning Let’s break them down 👇 #30DaysOfML

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Ife Abdulsamad | Organizing #careerfest26 @Ife_abdulsamad

11 months ago

🧵 🧠 Day 1/30 Intro to Machine Learning I’m starting my #30DaysOfML journey and I’ll be sharing what I learn each day in the simplest way I understand it. So here’s what Machine Learning means to me: 👇

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Sharon Kiprop @SharonKiprop21

over 1 year ago

✨ Day 30 is here! ✨ 30 days, 30 articles, and so much learning along the way. 💡 Grateful for everyone who joined me on this journey through the amazing world of Machine Learning. 👉 Check out: https://t.co/QT7GFgQC33 #MachineLearning #MLJourney #30DaysOfML #Gratitude

SharonKiprop21's tweet photo. ✨ Day 30 is here! ✨

30 days, 30 articles, and so much learning along the way. 💡 Grateful for everyone who joined me on this journey through the amazing world of Machine Learning.

👉 Check out: https://t.co/QT7GFgQC33

#MachineLearning #MLJourney #30DaysOfML #Gratitude https://t.co/MeOxQOw3S3

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AJ @AdityaJ5400

over 1 year ago

🚀 Starting #30DaysOfML Interview Prep! Join me for daily ML interview questions & tips to boost your prep! Day 28: How does dropout prevent overfitting in deep neural networks? #MachineLearning #MLInterview #DataScience

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AJ @AdityaJ5400

over 1 year ago

🚀 Starting #30DaysOfML Interview Prep! Join me for daily ML interview questions & tips to boost your prep! Day 27: Explain the concept of Markov Chains and their applications. #MachineLearning #MLInterview #DataScience

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AJ @AdityaJ5400

over 1 year ago

🚀 Starting #30DaysOfML Interview Prep! Join me for daily ML interview questions & tips to boost your prep! Day 26: What is a Bayesian Network, and where is it applicable? #MachineLearning #MLInterview #DataScience

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AJ @AdityaJ5400

over 1 year ago

🚀 Starting #30DaysOfML Interview Prep! Join me for daily ML interview questions & tips to boost your prep! Day 24: What is the KL Divergence, and how is it used in ML? #MachineLearning #MLInterview #DataScience

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AJ @AdityaJ5400

over 1 year ago

🚀 Starting #30DaysOfML Interview Prep! Join me for daily ML interview questions & tips to boost your prep! Day 20: What are the limitations of reinforcement learning? #MachineLearning #MLInterview #DataScience

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AJ @AdityaJ5400

over 1 year ago

🚀 Starting #30DaysOfML Interview Prep! Join me for daily ML interview questions & tips to boost your prep! Day 19: How do autoencoders perform dimensionality reduction, and when are they used? #MachineLearning #MLInterview #DataScience

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AJ @AdityaJ5400

over 1 year ago

🚀 Starting #30DaysOfML Interview Prep! Join me for daily ML interview questions & tips to boost your prep! Day 18: Describe the difference between Generative and Discriminative models. #MachineLearning #MLInterview #DataScience

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AJ @AdityaJ5400

over 1 year ago

🚀 Starting #30DaysOfML Interview Prep! Join me for daily ML interview questions & tips to boost your prep! Day 17: Explain Batch Normalization and its benefits. #MachineLearning #MLInterview #DataScience

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AJ @AdityaJ5400

over 1 year ago

🚀 Starting #30DaysOfML Interview Prep! Join me for daily ML interview questions & tips to boost your prep! Day 16: How do CNNs handle spatial hierarchies in image data? #MachineLearning #MLInterview #DataScience

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