Machine Learning Basics practice
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1. Practice Machine Learning Basics overview by building one step of a small real project feature and checking the result.
code-writing1. Start from the Machine Learning Basics 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 Basics setup by building one step of a small real project feature and checking the result.
code-fix1. Start from the Machine Learning Basics 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 Basics syntax by building one step of a small real project feature and checking the result.
output1. Start from the Machine Learning Basics 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 Basics examples by building one step of a small real project feature and checking the result.
fill-blank1. Start from the Machine Learning Basics 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 Basics workflow by building one step of a small real project feature and checking the result.
true-false1. Start from the Machine Learning Basics 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 Basics validation by building one step of a small real project feature and checking the result.
mini-project1. Start from the Machine Learning Basics 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 Basics debugging by building one step of a small real project feature and checking the result.
mcq1. Start from the Machine Learning Basics 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 Basics best practices by building one step of a small real project feature and checking the result.
code-writing1. Start from the Machine Learning Basics 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 Basics overview by building one step of a small real project feature and checking the result.
code-fix1. Start from the Machine Learning Basics 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 Basics setup by building one step of a small real project feature and checking the result.
output1. Start from the Machine Learning Basics 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 Basics syntax by building one step of a small real project feature and checking the result.
fill-blank1. Start from the Machine Learning Basics 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 Basics examples by building one step of a small real project feature and checking the result.
true-false1. Start from the Machine Learning Basics 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 Basics workflow by building one step of a small real project feature and checking the result.
mini-project1. Start from the Machine Learning Basics 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 Basics validation by building one step of a small real project feature and checking the result.
mcq1. Start from the Machine Learning Basics 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 Basics debugging by building one step of a small real project feature and checking the result.
code-writing1. Start from the Machine Learning Basics 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 Basics best practices by building one step of a small real project feature and checking the result.
code-fix1. Start from the Machine Learning Basics 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 Basics overview by building one step of a small real project feature and checking the result.
output1. Start from the Machine Learning Basics 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 Basics setup by building one step of a small real project feature and checking the result.
fill-blank1. Start from the Machine Learning Basics setup lesson example.
2. Use sample input, output and edge cases instead of placeholder text.
3. Run the example and compare output before polishing.