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 ๐Ÿฆ‹ -> faster ๐ŸŽ๏ธ -> cheaper ๐Ÿ’ธ file format to...

I'm sure you've used data augmentation before. Most people think of data augmentation as a technique to improve their model during training. This is true, but they are missing s...

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How can you learn Machine Learning faster? ๐Ÿค” 2 are the key ingredients. Let me explain.

While research papers certainly should split train/test temporally (their goals are to assess method validity), ML performance evaluation is a bit different for production (& shoul...

Over 55,000+ research papers are being published each year in Machine Learning. It's getting CRAZY. How do you even know what to pay attention to? Here are 5 tactics we've lear...

I hand-picked 7+1 free online courses that'll teach you all the math you need in machine learning. Use these to build substantial math knowledge from zero:

I've helped hundreds of people start with machine learning. Everyone asks me the same, fundamental question. But they all hate my answer. Engineers even more. Let me try again,...

Learn Excel for free ๐Ÿคฏ. Excel is used in data analysis Bookmark this thread A thread๐Ÿงต๐Ÿ‘‡

Tired of spending countless hours trying to generate the training data for your ML models? Let me share 3 tips to increase your productivity, in another mega ๐Ÿงต

College completely failed to teach me data analysis. So I spent over 10,000 hours learning Python. Then, I picked the 13 best libraries for machine learning and data analysis. B...

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One of the most common problems in machine learning: How do you deal with imbalanced datasets? Not only does this happen frequently, but it's also a popular interview question....

Understanding different roles in data science; Who does what? A thread ๐Ÿงต ๐Ÿ‘‡ https://t.co/leMYLPmDDx

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If you are still confused about Artificial Intelligence, Machine Learning, Deep Learning, and Data Science Let's sort it out with this thread Understand the difference between AI,...

Many people new to machine learning have no idea that labeling data is a problem they need to think about. To be clear: "labeled datasets" aren't a thing in the real world. Here...

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๐Ÿ Essential Cheat Sheets for Machine Learning and Deep Learning Engineers (with Python)๐Ÿ“‘ 1. Keras 2. Numpy 3. Pandas 4. Scipy 5. Matplotlib 6. Scikit-learn 7. Neural Networks Zoo...

There is one big reason we love the logarithm function in machine learning. Logarithms help us reduce complexity by turning multiplication into addition. You might not know it, bu...

Here is what Machine Learning tutorials told you to do: 1. Start by transforming your dataset 2. Then split it (train, validation, and test sets) 3. Finally, build your model Ple...

Do you think that machines are already better than humans at processing and understanding images? I did. Until I realized it is possible to deceive a state-of-the-art model, like...

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Every machine learning course talks about splitting your data. Surprisingly, many people don't understand how to use each set properly. Let's talk about some of the things you sh...