Machine Learning

𝗙𝗲𝗮𝘁𝘂𝗿𝗲 𝗜𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝗰𝗲 measures the contribution of each feature to the model's predictions. It is crucial in Machine Learning for several reasons. Let's see them 🧵👇 https://t.co/LQj...

David Andrés 🤖📈🐍

@daansan_ml

A problem with large neural networks: They look like a mess. Chaos leads to issues. Here is a technique to introduce clarity 🔽 1/7 https://t.co/MJi55B7FKC

Levi

@levikul09

SHAP is a powerful technique in machine learning for interpreting the output of complex models. Commonly used for ✨Feature Engineering✨ Let's explore SHAP further 🧵 👇 https://t.c...

David Andrés 🤖📈🐍

@daansan_ml

Best YouTube channels for Data Science: ❯ Python ➟ Corey Schafer ❯ SQL ➟ Joey Blue ❯ MS Excel ➟ Chandoo ❯ PowerBI ➟ Guy in a Cube ❯ Data Analyst ➟ AlexTheAnalyst ❯ Mathematics ➟ 3...

Swapna Kumar Panda

@swapnakpanda

K-Nearest Neighbours (KNN), clearly explained:

Akshay 🚀

@akshay_pachaar

Logistic regression is not used for regression! Let me explain: 1/8

Levi

@levikul09

What is the difference between Classification and Regression in Machine Learning? 🤔 🧵 👇 https://t.co/Bnfw8Qjx86

David Andrés 🤖📈🐍

@daansan_ml

Are you a data scientist using CSV files to store your data? What if I told you there is a better way? Can you imagine a -> lighter 🦋 -> faster 🏎️ -> cheaper 💸 file format to s...

Pau Labarta Bajo

@paulabartabajo_

No Google Colab, No Jupyter Notebook! Introducing Simple ML for Sheets. Let's build Machine Learning Models right inside Google Sheets. Thread🧵👇 https://t.co/VSyLcY2lXN

Sumanth

@Sumanth_077

Survey of LLMs Reviews three popular families of LLMs (GPT, Llama, PaLM), their characteristics, contributions, and limitations. Includes a summary of capabilities and techniques...

elvis

@omarsar0

You can forecast Time Series data using a Machine Learning algorithm like XGBoost or Random Forest. However, you need to reframe your problem as a Supervised Learning one. Learn...

David Andrés 🤖📈🐍

@daansan_ml

Real world ML is all about dealing with imbalanced datasets! Try SMOTE - it works like magic... 🪄 https://t.co/JuViysw1Kk

Akshay 🚀

@akshay_pachaar

5 classification models to start with:

Levi

@levikul09

10 great Python packages for Data Science not known to many:

Akshay 🚀

@akshay_pachaar

Linear Regression clearly explained:

Levi

@levikul09

Missing data kills Machine Learning models. But pseudocounts can save them! Let's see how 🔽 🧵 https://t.co/4LZpn1MJsj

Levi

@levikul09

How LLMs work, clearly explained:

Akshay 🚀

@akshay_pachaar

K-Means is the simplest clustering algorithm. Here is how it works 🔽 1/6 https://t.co/MFh8ei1MfU

Levi

@levikul09

Google has released 7 free courses on AI for Developers. No payment required! Here are 7 FREE Google Developer courses to learn AI in 2024 https://t.co/UWqfLCUq8Y

Srikeerthan Reddy

@srikerthanreddy

@bassemelnour Adam.ai- NLP, ML, Embedded Systems Affectiva - ML, Computer Vision, Speech Projects Agolo - NLP, ML AtomicaAI - ML, Computer Vision, 3D Graphics Avelabs - ML, Compute...

Ahmed Nasr

@AhmedNasr_

Type I error is a false positive conclusion, while a Type II error is a false negative conclusion. Let's understand the confusion matrix:

Sasi 📊📈

@freest_man

Outliers do not fit in with the rest of the data. But how can an ML model identify them? Let me introduce one-class classification. 1/6 https://t.co/T6HqA4W1yE

Levi

@levikul09

How does the Decision Tree model choose the best questions? Gini impurity index 🧵 https://t.co/VLHiwRajHP

Levi

@levikul09

5 facts about Tanh. Tanh is an activation function used in complex Neural Networks. Here are some facts you must know about it. 🧵 https://t.co/E9HnpC7EpY

Levi

@levikul09