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JustML finds the right scikit-learn or xgboost estimator for a given supervised machine learning problem, along with the optimal hyperparameters.
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I counted the number of board games published every year and mapped it on a plot. It greatly demonstrates the current growth trend of the board game industry. #Kaggle #KernelsAward #boardgames #data #boardgamegeek
Pseudo code is used to solve the Fibonaci problem and other problems in this post, so readers using any programming languages can read it. Comments and other solutions using any other programming languages are welcome!
What are the critical steps to get a job in data science? We share the proven formula that helped many data enthusiasts secure job offers as data scientist/analyst, data engineer and machine learning engineer.
You are absolutely right. Our main idea was to show how RNNs could be used for time series forecasting. We have chosen public bitcoin price data because this problem is well-known for general public. There is no doubt, that such difficult problem cound be solved using only previous prices. But this article may be a good starting point to understand potential methods to approach such problems.
To be honest, I don’t think any of these books are really very useful. I’ve been doing data science professionally for over two years, and if I had to go back in time and advice myself to read some of the books on data science, it wouldn’t be any of these. I would recommend ESL or ISL (books and youtube lectures), Max Kuhn’s book, doing some live tutorials of scikit-learn, data.table and pandas “5-minute” vignettes, and just going straight into Kaggle.
Data Science at the Command Line comes close, though. I’ve looked at that book early enough, and it has some nice CL tools that were very helpful.
Predicting markets with machine learning is always dangerous, because unlike most types of statistics, markets do not evidently have a single representation that is slowly uncovered; "gravity can flip upside down overnight".
The channel has regular Data Science updates from a lot of different sources (at least twice per day)
Also, anyone interested can join a Data Science discussion group in Telegram for English speakers: