th.
good
96 Matching Annotations
- Mar 2023
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katiemacalintal.github.io katiemacalintal.github.io
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doabell.github.io doabell.github.io
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maybe I'm not finding it but is your source code linked?
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nice plots to take a deeper dive into what is happening
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e:
nice job narrowing what you are working with
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Adelie.
good catch
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?
good job guiding your workflow
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s.
good start
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github.com github.com
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)
good job
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:
nice to have docstrings or comments describing code
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eduparlema.github.io eduparlema.github.io
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gamma is independent from the noise!
great takeaway
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e.
good job walking through your thought process
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el.
good analysis
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.
nice
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t.
good background information
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github.com github.com
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set)
looks good
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s2)
use docstrings to explain functions instead of comments and save comments
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bridgetulian.github.io bridgetulian.github.io
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ta).
nice analysis
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use
what does this show
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ad
what does this show?
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d
what is this
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.
nice walkthrough of your approach
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miatarantola.github.io miatarantola.github.io
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t
where is source code
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h size
elaborate more on what experiment will be testing, not just saying batch size
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a
nice analysis
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ss
nice procedure
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)
looks good
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odel
nice docstrings
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hedavam.github.io hedavam.github.io
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:
hyperlink
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()
put comments in code
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n
nice broad takeaways. could expain a little and then say the big takeaway
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e perceptron
perceptron?
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github.com github.com
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ak
good job
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nice organization
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w
great docstrings
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eduparlema.github.io eduparlema.github.io
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.
other big takeaways overall?
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elaborate
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.
elaborate a little more on why
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t.
nice job building off findings
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y
good comments
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.
nice background setup
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github.com github.com
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s
good job
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:
need docstrings explaining what functions are doing
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aidmmcmillan.github.io aidmmcmillan.github.io
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.
good experiments
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:
could elaborate on findings
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.
good job explaining your experiment before you do it
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.
what properties of with and without momentum make the graphs behave like this?
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katiemacalintal.github.io katiemacalintal.github.io
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you kind of just stop after your plots, there was no analysis of the experiments. This part is crucial. Also have docstrings for what you're doing in each experiment. Helpful to title each experiment and what youre doing
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.
good
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t it
what
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.
why
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Before we set our alpha to 0.1, but if we use th
sentence grammar
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.
good analysis
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reasonable
what does reasonable learning rate mean in this context? Say what the learning rate is and why
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github.com github.com
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ly
nice comments
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on.
good use of docstrings throughout
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#convert the actual y into -1 or 1
nice comments
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k
great job!
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sallyliubj.github.io sallyliubj.github.io
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.
good
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self.w = self.w + (y_[i]y_predict[i]<0)y_[i]*X_[i]
latex?
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.
any other big takeaways?
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Experimentation
You can make headers
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:
it would be good to include an intro with some background and the objective of what you are doing
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:
good practice to include docstrings/comments
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np.insert
good use of numpy operations
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trongdle.github.io trongdle.github.io
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.
good
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1
could describe what experiment 1 is here
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a.
great background and objective
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github.com github.com
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:
docstrings/comments are good practice
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w
good job!
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kate-kenny.github.io kate-kenny.github.io
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. Hence, we must multiply the runtime by p.
good
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C
what do these plots indicate?
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The fit()
great intro explanation
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d
?
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github.com github.com
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.
you could give more detail. Its good practice to have thorough docstrings so anyone (including you in a while) can read them and understand exactly what is going on
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jackgreenburg.github.io jackgreenburg.github.io
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)
explain what these plots indicate
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y.
Before this, it would be good to include an intro on what the goal of this blog post is.
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accuracy
concise code, good
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)
good use of numpy operations
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l
good job commenting code. Docstrings/comments are good habits
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madgallop.github.io madgallop.github.io
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.
It would be good if you could explain everything a little more along the way. This is a blog post, which means there should be more writing explaining every step of your thought process.
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.
good intro
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y
written twice, could be hyperlink
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(np.multiply
good use of numpy operations
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steps.
great description
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wrifro.github.io wrifro.github.io
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0
including docstrings/comments describing what the code is doing is good practice
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.
good key point
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.
great visuals
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1.0
Mention what this represents
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L
A quick intro about what you are going to do and what this blog post is about would be helpful
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github.com github.com
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np.dot
good use of numpy operations
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'''
good docstrings
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dcruzeneil.github.io dcruzeneil.github.io
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!
great summary
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Therefore, we can tell that if the data is not linearly separable - the perceptron does not converege!
key point--good
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!
good job!
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0.
good explanation
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.
Very clear intro
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