Hi everyone, I’ve studied Machine Learning before, but this is my first time doing Deep Learning on this platform. The lectures focus mostly on theory, and I’m finding it hard to connect that to the coding assignments. Unlike my previous ML course, there’s not much guidance on how to implement the code step by step.
Are we expected to figure out the implementation ourselves based on the theory? Or is there a recommended way to approach the assignments if you’re new to this format?
Appreciate any tips or resources that helped you get started!
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Instructions are given in the assignment notebook. This specialization assumes that you are already familiar with programming, though not an expert. If you are stuck in the assignment or code or anything, you can ask here (without sharing your code). But you can share the full error that you are getting.
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Have you actually looked at the first two assignments in Week 2 of DLS Course 1? As Saif says, they give you quite complete instructions and explanations of what it is you need to do. They repeat the math formulas from the lectures. They even give you template code so that you only have to fill in the particular lines of code that implement the core of each algorithm, instead of having to create everything from scratch. They have done the work of structuring each exercise as a set of modular functions that implement all the key algorithms. You just have to complete the core code for each function.
Please try the assignments and make sure to read everything completely. “Saving time” by skipping reading the instructions in detail will very likely not end up being a net savings of time. 
Let us know if you encounter any questions that you feel are not covered by the instructions.
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