Learn the basics of Data Science in the crash course. You will learn about the theory and code behind the most common algorithms used in data science.

💻 Code: https://github.com/marcopeix/datasciencewithmarco
💻 Datasets: https://github.com/marcopeix/datasciencewithmarco/tree/master/data

⭐️ Course Contents ⭐️
⌨️ (00:00) Introduction
⌨️ (03:06) Setup
⌨️ (04:29) Linear regression (theory)
⌨️ (09:29) Linear regression (Python)
⌨️ (20:59) Classification (theory)
⌨️ (30:16) Classifiaction (Python)
⌨️ (49:30) Resampling & regularization (theory)
⌨️ (56:09) Resampling and regularization (Python)
⌨️ (1:05:17) Decision trees (theory)
⌨️ (1:13:12) Decision trees (Python)
⌨️ (1:24:50) SVM (theory)
⌨️ (1:28:17) SVM (Python)
⌨️ (1:58:24) Unsupervised learning (theory)
⌨️ (2:06:54) Unsupervised learning (Python)
⌨️ (2:20:55) Conclusion

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Data Science Hands-On Crash Course
3.00 GEEK