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Machine Learning Engineering (16 weeks)
Full-Stack Software Developer
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Curated list of small interactive and incremental exercises you can take to get better at any coding skill.
Curated section of projects to build while learning with simple instructions, videos, solutions and more.
Guides on different topics related to the technologies that we teach in our courses
Social & live learning
The most efficient way to learn: Join a cohort with classmates just like you, live streams, impromptu coding sessions, live tutorials with real experts, and stay motivated.
Finally, you already have all the necessary knowledge to prepare a real dataset to later train a machine learning model, which you will learn throughout the bootcamp.
It is intended that you apply all the knowledge learned with the other Numpy, Pandas, Matplotlib notebooks and even openCV that we will delve into later.
Feel free to add any additional analysis that you consider necessary and that is not raised in the questions.
This project comes with the necessary files to start working, so you just need to clone its repository to start. We strongly recomend using Gitpod to clone it by clicking here.
Please open this project in Gitpod, then, open the file
./project.ipynb that contains a series of exercises, compleate each of the exercises one by one.
Note: This exercise is not automatically graded.