Instructions
Write a brief reflection (roughly 250-300 words) on your learning this week:
- What did you actually do? (both in studio and on your own time)
- What did you learn from these activities?
- How does your work connect to course objectives?
- What questions or uncertainties remain?
Be specific about what you did and learned—avoid general statements about topics.
Annotated Example
(Note, this is intentionally fictional.)
This week I worked through the PyTorch tensor operations notebook during studio hours. (noting specific activity) The exercises helped me understand how matrix multiplication actually works in neural networks - especially how the dimension ordering affects the results. (connecting to Neural Computation pillar) I was stuck for a while on exercise 4 because I kept getting dimension mismatches, but working through it helped me realize I need to be really careful about tracking matrix shapes. (specific challenge and learning)
Outside of class, I read chapter 2 of the Chollet textbook and experimented with some of the code examples. (independent work) I noticed that many of the same tensor operations from our notebook showed up in the neural network implementations, which helped reinforce why we’re learning these fundamentals. (making connections)
This work is helping me progress toward the objective “implement basic neural network primitives efficiently” because I can now write vectorized operations instead of using loops. I can demonstrate this with my solutions to exercises 3-5. (explicit connection to course objective with evidence) However, I’m still unsure about when to use view() vs. reshape() - I’ll ask about this during next week’s studio. (identifying specific uncertainty and next step)
Tips & FAQ
“How do I connect my work to course objectives?”
Look for evidence in your work that demonstrates progress toward specific objectives:
- Code you wrote
- Problems you solved
- Concepts you can now explain
- Questions you can now answer
“What counts as being specific?”
| Instead of | Try |
|---|---|
| “I did the Python activity” | “I completed exercises 3-5 in the PyTorch notebook” |
| “I learned about neural nets” | “I can now explain how matrix multiplication works in a linear layer” |
| “The reading was helpful” | “The reading helped me understand why we use ReLU activations” |
“How do I write about things I’m still unsure about?”
It’s valuable to identify specific uncertainties:
- “I can do X, but I’m not sure how it relates to Y”
- “I’m confused about when to use X vs. Y”
- “I want to understand more about X”
“I’m not sure if I’ve met a specific objective yet”
Focus on concrete evidence:
- “My solution to problem X shows I can now do Y”
- “I can explain X to others, though I’m still working on Y”
- “I’m making progress on objective X because [specific evidence]”
You could paste the objective text and a screenshot of your evidence into a chatbot and have a conversation like “ask me some questions about my work to see if I’ve met this objective yet.”
“What if I’m not sure what to write about?”
Consider:
- What surprised you this week?
- What was harder or easier than expected?
- What connections did you notice between different topics?
- What would you like to understand better?
Common Pitfalls to Avoid
❌ “I learned about neural networks”
✅ “I practiced implementing a linear layer and learned how matrix shapes determine valid operations”
❌ “The reading was interesting”
✅ “The reading helped me understand [specific concept], though I’m still unclear about [specific point]”
❌ “I think I’ve mastered objective X”
✅ “My work on [specific task] shows progress toward objective X because [reason]”
Note: I used Claude to adapt instructions that I’d written earlier into this guide. Much of this text is AI-generated.