Machine Learning practice
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1. Practice Machine Learning overview by building one step of a small real project feature and checking the result.
code-writing1. Start from the Machine Learning overview lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
2. Practice Machine Learning setup by building one step of a small real project feature and checking the result.
code-fix1. Start from the Machine Learning setup lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
3. Practice Machine Learning syntax by building one step of a small real project feature and checking the result.
output1. Start from the Machine Learning syntax lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
4. Practice Machine Learning examples by building one step of a small real project feature and checking the result.
fill-blank1. Start from the Machine Learning examples lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
5. Practice Machine Learning workflow by building one step of a small real project feature and checking the result.
true-false1. Start from the Machine Learning workflow lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
6. Practice Machine Learning validation by building one step of a small real project feature and checking the result.
mini-project1. Start from the Machine Learning validation lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
7. Practice Machine Learning debugging by building one step of a small real project feature and checking the result.
mcq1. Start from the Machine Learning debugging lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
8. Practice Machine Learning best practices by building one step of a small real project feature and checking the result.
code-writing1. Start from the Machine Learning best practices lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
9. Practice Machine Learning overview by building one step of a small real project feature and checking the result.
code-fix1. Start from the Machine Learning overview lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
10. Practice Machine Learning setup by building one step of a small real project feature and checking the result.
output1. Start from the Machine Learning setup lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
11. Practice Machine Learning syntax by building one step of a small real project feature and checking the result.
fill-blank1. Start from the Machine Learning syntax lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
12. Practice Machine Learning examples by building one step of a small real project feature and checking the result.
true-false1. Start from the Machine Learning examples lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
13. Practice Machine Learning workflow by building one step of a small real project feature and checking the result.
mini-project1. Start from the Machine Learning workflow lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
14. Practice Machine Learning validation by building one step of a small real project feature and checking the result.
mcq1. Start from the Machine Learning validation lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
15. Practice Machine Learning debugging by building one step of a small real project feature and checking the result.
code-writing1. Start from the Machine Learning debugging lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
16. Practice Machine Learning best practices by building one step of a small real project feature and checking the result.
code-fix1. Start from the Machine Learning best practices lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
17. Practice Machine Learning overview by building one step of a small real project feature and checking the result.
output1. Start from the Machine Learning overview lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.
18. Practice Machine Learning setup by building one step of a small real project feature and checking the result.
fill-blank1. Start from the Machine Learning setup lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.