Machine Learning
1297 Threads
Junior data scientists stay inside Jupyter. Senior data scientists go beyond... ... so their ML models reach production π Wanna learn how? β
Broadcasting in NumPy is widely used, yet poorly understoodβοΈ Today, I'll clearly explain how broadcasting works! π Same rules apply to PyTorch & TensorFlow! A Thread π§΅π https:...
β Gradient Boosting and XGBoost explained in simple terms and how to use it ( with code). A quick thread π§΅ππ» #Python #DataScience #MachineLearning #DataScientist #Programming #C...
Looking for real-world ML project ideas? π‘ Let's build an ML system that predicts loan defaults. With π³ππΉπΉ ππΌππΏπ°π² π°πΌπ±π²π·πΎββοΈπ·β https://t.co/v9WULKJkyn
β LSTM and ARIMA model in Time Series Forecasting explained in simple terms and how to use it ( with code). A quick thread π§΅ππ» #Python #DataScience #MachineLearning #DataScientis...
𧡠Let's talk about encoding in data science! π€ Specifically, the difference between ordinal encoding and nominal encoding π https://t.co/ax6n7hq93x
Wow Microsoft have free beginner courses in Data Science, Machine Learning and AI (all on Github). Thats: - 34 Weeks of Learning - 70 Lessons - 52 Quizzes All for free?! Thank...
2 years ago I got tired of developing ML models... that never made it into production. Then I discovered this β
Backpropagation is fundamental in ANNs But how does it work? I will explain it now visually. 1/9 https://t.co/0ZBUwuTbPh
If you want to succeed in the future, you MUST learn AI. Here're 5 Courses on: β ChatGPT β Generative AI β Maching Learning To Teach you how to use AI Effectively. ππ
Wanna become an ML engineer? Then you need to build a π°πΌπΊπ½πΉπ²ππ² π π π½πΏπΌπ·π²π°π, and publish β the source code on GitHub, and β a public working app Here is an example π§ βββ
3 reasons why your XGBoost model does not work And 3 ways to solve them βββ https://t.co/g4p8PlNMPk
How to become a Data Scientist/Engineer in 3 months. AI has cancelled Excel, python, Data practitioners.. Learn python in 3 days. You see all the tweet above are far from rea...
A simple but effective ML technique β K-Nearest Neighbors (KNN) algorithm. It can be applied to a variety of real-world problems. Let me explain how it works. 𧡠1/8 https://t.c...
We've all dealt with activation functions while working with neural nets. - Sigmoid - Tanh - ReLu & Leaky ReLu - Gelu Ever wondered why they are so importantβπ€ Let me explain it...
Wanna land a Machine Learning job? Build ONE project that solves ONE real-world problem π 3 steps to find the right problem for you π€β
Don't pay ridiculous amount of money to learn Data Science & Machine Learning. Access FREE Data Science Education from: β― MIT β― CMU β― Stanford β― DeepMind β― Cornell Tech A Thread...
XGBoost is one of the most effective algorithms for time-series prediction. But, you need to prepare your data carefully. These are the steps to transform raw data into supervise...
Gradient descent, vanishing gradients, exploding gradients... Gradients are everywhere in ML. But what does Gradient mean? Let me explain! 𧡠1/10 https://t.co/vYXBGpXdd4
Stanford offers FREE Data Science Education! World-class courses on: - Machine Learning - Computer Vision - Statistical Learning - Graph Neural Networks - Reinforcement Learning...
If you are looking to learn Data Science and Machine Learning, effectively this website is an absolute gold mine. This explains the most technical and theoretical concepts in Data...
I was recently on a panel with several other professors and we were asked to give some tips to graduate students in machine learning. It got me thinking about why professors are so...
Running a Machine Learning model on your laptop localhost DOES NOT move any business metrics. So it has 0 value. π΅ My advice? Learn to deploy ML models. Here are 2 strategies to...
10 ways to use machine learning in trading (with the Python library): https://t.co/7OqB06q38t
