From cfdd0447bf3f53a4cd4df1f4fad2fafb704352bd Mon Sep 17 00:00:00 2001 From: Sarah M Brown Date: Wed, 14 Oct 2020 20:28:55 -0400 Subject: [PATCH 1/9] empty file --- assignments/06-naive-bayes.md | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 assignments/06-naive-bayes.md diff --git a/assignments/06-naive-bayes.md b/assignments/06-naive-bayes.md new file mode 100644 index 00000000..e69de29b From 25723d0ae5e9f71828fc7bf1647592ce0e20e24b Mon Sep 17 00:00:00 2001 From: Sarah M Brown Date: Fri, 16 Oct 2020 13:57:29 -0400 Subject: [PATCH 2/9] after class notes --- notes/2020-10-16.md | 114 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 114 insertions(+) create mode 100644 notes/2020-10-16.md diff --git a/notes/2020-10-16.md b/notes/2020-10-16.md new file mode 100644 index 00000000..fdaba60c --- /dev/null +++ b/notes/2020-10-16.md @@ -0,0 +1,114 @@ +--- +jupytext: + text_representation: + extension: .md + format_name: myst + format_version: 0.12 + jupytext_version: 1.6.0 +kernelspec: + display_name: Python 3 + language: python + name: python3 +--- + +# Class 17: Evaluating Classification and Midsemester Feedback + +1. share your favorite rainy day activity (or just say hi) in the zoom chat for attendance +1. log onto prismia + ++++ + + +## Naive Bayes Review + + +Main assumptions: +- classification assumes that features will separate the gorups +- NB: conditionally independent + +```{code-cell} ipython3 +# %load http://drsmb.co/310 +import pandas as pd +import seaborn as sns +from sklearn.model_selection import train_test_split +from sklearn.naive_bayes import GaussianNB +``` + +```{code-cell} ipython3 +iris = sns.load_dataset("iris") +iris.head() +``` + +```{code-cell} ipython3 +X_train, X_test, y_train, y_test = train_test_split(iris.values[:,:4], + iris.species.values, + test_size=0.5, random_state=0) +``` + +```{code-cell} ipython3 +gnb = GaussianNB() +y_pred = gnb.fit(X_train, y_train).predict(X_test) +``` + +```{code-cell} ipython3 +y_pred +``` + +```{code-cell} ipython3 +y_test +``` + +```{code-cell} ipython3 +sum(y_pred == y_test) +``` + +```{code-cell} ipython3 +len(y_pred) +``` + +```{code-cell} ipython3 +gnb.score(X_test, y_test) +``` + +```{code-cell} ipython3 +71/75 +``` + +```{code-cell} ipython3 +from sklearn.metrics import confusion_matrix, classification_report +``` + +```{code-cell} ipython3 +confusion_matrix(y_test,y_pred,) +``` + +```{code-cell} ipython3 +sns.pairplot(data =iris, hue='species') +``` + +```{code-cell} ipython3 +print(classification_report(y_test,y_pred)) +``` + +```{code-cell} ipython3 +gnb.__dict__ +``` + +```{code-cell} ipython3 +import numpy as np +``` + +```{code-cell} ipython3 +# %load http://drsmb.co/310 +df = pd.DataFrame(np.concatenate([np.random.multivariate_normal(mu, sig*np.eye(4),20) + for mu, sig in zip(gnb.theta_,gnb.sigma_)])) +df['species'] = [ci for cl in [[c]*20 for c in gnb.classes_] for ci in cl] +sns.pairplot(data =df, hue='species') +``` + + +## Reminder to Stop Early for [feedback survey](https://forms.gle/yqWEPGJjFXDczuDv7) + +```{code-cell} ipython3 + +``` From 3a601735740adbdb3d09e27be136a72b390a20e1 Mon Sep 17 00:00:00 2001 From: Sarah M Brown Date: Fri, 16 Oct 2020 16:06:28 -0400 Subject: [PATCH 3/9] more revs --- assignments/06-naive-bayes.md | 33 +++++++++++++++++++++++++++++++++ 1 file changed, 33 insertions(+) diff --git a/assignments/06-naive-bayes.md b/assignments/06-naive-bayes.md index e69de29b..f6f9f661 100644 --- a/assignments/06-naive-bayes.md +++ b/assignments/06-naive-bayes.md @@ -0,0 +1,33 @@ +# Assignment 6 + + +__Due: 2020-10-20__ + + +Remember, even if you aren't sure how to do every part of the assignment, submitting pseudocode, a list of your questions indicating where you got stuck, or a partial solution will get you personalized feedback. You might even earn level 1 achievements for the partial effort. + +## For Classification Level 2: + +[Submission template](https://classroom.github.com/a/fojgz8Cc) + +1. Choose two datasets with continuous valued features and a categorical target value save them to the data folder. We recommend the [UCI Data Repository](https://archive.ics.uci.edu/ml/index.php) +1. Load the data using the relative path. +1. Use exploratory data analysis to evaluate if Gaussian Naive Bayes is a good fit, based on its core assumptions +1. Confirm your predictions by fitting the classifier and evaluating its performance. + + +Use Markdown headings to introduce each dataset and description of the data, including its source, with a link. Include explanatory text at each step of your analysis. + + + + +_if you have dataset that you're interested in that's got categorical or binary features only, you can try a different naive Bayes classifier. You still need to assess if the naive bayes assumption holds or not. Look into mutual information_ + +## For construct level 2 + +1. Make your own dataset for classification by merging unrelated data that you're interested in or querying a database + + +## Summarize and Viz level 2 + +Show some extra summary stats or plots From 733a40dcc66b9a709f499cc57c122c3e223940d5 Mon Sep 17 00:00:00 2001 From: Sarah M Brown Date: Sat, 17 Oct 2020 00:15:44 -0400 Subject: [PATCH 4/9] assignment 6 ready to check --- assignments/06-naive-bayes.md | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/assignments/06-naive-bayes.md b/assignments/06-naive-bayes.md index f6f9f661..68205011 100644 --- a/assignments/06-naive-bayes.md +++ b/assignments/06-naive-bayes.md @@ -10,13 +10,19 @@ Remember, even if you aren't sure how to do every part of the assignment, submit [Submission template](https://classroom.github.com/a/fojgz8Cc) -1. Choose two datasets with continuous valued features and a categorical target value save them to the data folder. We recommend the [UCI Data Repository](https://archive.ics.uci.edu/ml/index.php) +You're going to train a Gaussian Naive Bayes classifier five total times in this assignment in two notebooks. + +1. Create one notebook where you load and answer the following for each of the four provided datasets with exploratory data analysis. Then fit and evaluate a Gaussian Naive Bayes classifier. + - Does it meet the assumptions for Gaussian Naive Bayes? + - If not which assumptions does it break? + - Do you expect Gaussian Naive Bayes to work well on this dataset, why or why not? +1. Create a second notebook where you evaluated a dataset of your choice with continuous valued features and a categorical target value save them to the data folder. Include a description of the data, including its source, with a link. We recommend the [UCI Data Repository](https://archive.ics.uci.edu/ml/index.php) 1. Load the data using the relative path. 1. Use exploratory data analysis to evaluate if Gaussian Naive Bayes is a good fit, based on its core assumptions 1. Confirm your predictions by fitting the classifier and evaluating its performance. -Use Markdown headings to introduce each dataset and description of the data, including its source, with a link. Include explanatory text at each step of your analysis. +Include explanatory text at each step of your analysis. @@ -25,7 +31,7 @@ _if you have dataset that you're interested in that's got categorical or binary ## For construct level 2 -1. Make your own dataset for classification by merging unrelated data that you're interested in or querying a database +1. As your chosen dataset, build your own dataset for classification by merging two data files that you're interested in or querying a database. ## Summarize and Viz level 2 From 34de729841dc98bb2b8cfc7e3aed416e381d977b Mon Sep 17 00:00:00 2001 From: Sarah M Brown Date: Sun, 18 Oct 2020 15:09:07 -0400 Subject: [PATCH 5/9] simplify --- assignments/06-naive-bayes.md | 23 +++++++++-------------- 1 file changed, 9 insertions(+), 14 deletions(-) diff --git a/assignments/06-naive-bayes.md b/assignments/06-naive-bayes.md index 68205011..51541316 100644 --- a/assignments/06-naive-bayes.md +++ b/assignments/06-naive-bayes.md @@ -8,32 +8,27 @@ Remember, even if you aren't sure how to do every part of the assignment, submit ## For Classification Level 2: -[Submission template](https://classroom.github.com/a/fojgz8Cc) +[Acccept the Assignment](https://classroom.github.com/a/fojgz8Cc) -You're going to train a Gaussian Naive Bayes classifier five total times in this assignment in two notebooks. -1. Create one notebook where you load and answer the following for each of the four provided datasets with exploratory data analysis. Then fit and evaluate a Gaussian Naive Bayes classifier. - - Does it meet the assumptions for Gaussian Naive Bayes? - - If not which assumptions does it break? - - Do you expect Gaussian Naive Bayes to work well on this dataset, why or why not? -1. Create a second notebook where you evaluated a dataset of your choice with continuous valued features and a categorical target value save them to the data folder. Include a description of the data, including its source, with a link. We recommend the [UCI Data Repository](https://archive.ics.uci.edu/ml/index.php) -1. Load the data using the relative path. -1. Use exploratory data analysis to evaluate if Gaussian Naive Bayes is a good fit, based on its core assumptions -1. Confirm your predictions by fitting the classifier and evaluating its performance. +Create one notebook where you load examine each of the provided datasets for for suitability to use with Gaussian Naive Bayes. Label the sections `Dataset #`. Use exploratory data analysis (visualisation and statistics) in pandas and Gaussian Naive Bayes from scikit learn to answer the following for each dataset: -Include explanatory text at each step of your analysis. + +1. Do you expect Gaussian Naive Bayes to work well on this dataset, why or why not? (think about the assumptions of naive bayes and classification in general) _explanation is essential here, because you can actually use the classifier to check_ +1. How well does a Gaussian Niave Bayes classifier work on this dataset? Do you think a different classifier might work better or do you think this data cannot be predicted any better than this? +1. How does the actual performance compare to your prediction? If it performs much better or much worse than you expected, what might you use to figure out why? (_you do not have to figure out why your predictions were not correct, just list tools you've learned in class that might help you figure that out_) +Include explanatory text at each step of your analysis. -_if you have dataset that you're interested in that's got categorical or binary features only, you can try a different naive Bayes classifier. You still need to assess if the naive bayes assumption holds or not. Look into mutual information_ ## For construct level 2 -1. As your chosen dataset, build your own dataset for classification by merging two data files that you're interested in or querying a database. +Build your own dataset for classification by merging data from separate sources that you're interested in. ## Summarize and Viz level 2 -Show some extra summary stats or plots +Show some extra summary stats and plots From d2b44c3ebc2bde49a1fb5725788eb9329eab247e Mon Sep 17 00:00:00 2001 From: Sarah M Brown Date: Sun, 18 Oct 2020 15:12:47 -0400 Subject: [PATCH 6/9] links --- _toc.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/_toc.yml b/_toc.yml index 964c3d22..88e74953 100644 --- a/_toc.yml +++ b/_toc.yml @@ -37,6 +37,7 @@ - file: assignments/03-exploratory - file: assignments/04-prepare - file: assignments/05-construct + - file: assignments/06-naive-bayes - file: portfolio/index sections: From 497f7a18102d15bc6d46b5a8541f576a84561de4 Mon Sep 17 00:00:00 2001 From: Sarah M Brown Date: Sun, 18 Oct 2020 15:29:26 -0400 Subject: [PATCH 7/9] hint and git --- assignments/06-naive-bayes.md | 47 ++++++++++++++++++++++++++++-- notes/data/feedback_structured.csv | 15 ++++++++++ 2 files changed, 60 insertions(+), 2 deletions(-) create mode 100644 notes/data/feedback_structured.csv diff --git a/assignments/06-naive-bayes.md b/assignments/06-naive-bayes.md index 51541316..cb4b4417 100644 --- a/assignments/06-naive-bayes.md +++ b/assignments/06-naive-bayes.md @@ -16,11 +16,54 @@ Create one notebook where you load examine each of the provided datasets for for 1. Do you expect Gaussian Naive Bayes to work well on this dataset, why or why not? (think about the assumptions of naive bayes and classification in general) _explanation is essential here, because you can actually use the classifier to check_ -1. How well does a Gaussian Niave Bayes classifier work on this dataset? Do you think a different classifier might work better or do you think this data cannot be predicted any better than this? +1. How well does a Gaussian Naive Bayes classifier work on this dataset? Do you think a different classifier might work better or do you think this data cannot be predicted any better than this? 1. How does the actual performance compare to your prediction? If it performs much better or much worse than you expected, what might you use to figure out why? (_you do not have to figure out why your predictions were not correct, just list tools you've learned in class that might help you figure that out_) -Include explanatory text at each step of your analysis. +This assignment will be easiest if you take advantage of the template via git: + +### Git Workflow + +1. Click the green code button and copy the url. +1. clone the repository as below where th eurl is the one you copied from GitHub. In your terminal on Linux or Mac or on the GitBash on Windows ([install instructions on tools section of syllabus](prorgrammin-env) ) + + ``` + cd path/where/you/want/a/new/folder/for/this/assignment + git clone http://github.com/rhodyprog4ds/06-classification-username + ``` + +1. then launch your notebook from the newly created folder. + + on Linux or Mac, in the same terminal (remember you can use tab complete) + ``` + cd 06-classification + jupyter notebook + ``` + or on windows, in your Anaconda prompt + ``` + cd path/where/you/want/a/new/folder/for/this/assignment/06-classification-username + jupyter notebook + ``` + +1. work on your assignment, by opening the notebooks there and editing them. +1. commit your changes when you want to save a point in your progress. Either you have part workign and want to save that, or you want feedback, or you're done. On whichever terminal you used for the `git clone` command above + + ``` + git add . + git commit -m 'description of your changes since las commit' + ``` + +1. push your changes when you want to share them on GitHub, (eg need help, want feedback or complete) + + ``` + git push + ``` + +1. if you will keep working after pushing, first pull down the .md conversion that was added by GitHub actions. If you don't you'll have to merge, it should be fine, but ask if you're not sure. + + ``` + git pull + ``` diff --git a/notes/data/feedback_structured.csv b/notes/data/feedback_structured.csv new file mode 100644 index 00000000..0b77eedd --- /dev/null +++ b/notes/data/feedback_structured.csv @@ -0,0 +1,15 @@ +How much do you think you've learned so far this semester?,How much of the material that's been taught do you feel you understand?,How do you think the achievements you've earned so far align with your understanding?,Rank the following as what you feel the grading (when you do/not earn achievements) so far actually reflects about your performance in the class [How well I follow instructions],Rank the following as what you feel the grading (when you do/not earn achievements) so far actually reflects about your performance in the class [What I understand about the material],Rank the following as what you feel the grading (when you do/not earn achievements) so far actually reflects about your performance in the class [How much effort I put into assignments],How fair do you think the amount each of the following is reflected in the grading [How well I follow instructions],How fair do you think the amount each of the following is reflected in the grading [What I understand about the material],How fair do you think the amount each of the following is reflected in the grading [How much effort I put into assignments],Which of the following have you done to support your learning outside of class? +4,3,I think they reflect my understanding well,Reflected moderately in the grading,Reflected strongly in the grading,Reflected perfectly in the grading,Is fairly reflected in the grading,Should be reflected more in the grading,Should be reflected more in the grading,"read the notes online, download and run the notes" +4,4,I think the achievements underestimate what I know (I know more than they reflect),Reflected strongly in the grading,Reflected strongly in the grading,Reflected moderately in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Should be reflected more in the grading,"read the notes online, download and run the notes, reading the documentation or course text, reading blogs or tutorials I find on my own, watching videos that I find on my own, solving extra questions in the class notes, tinkering with code to answer other aspects of the material that I'm curious about" +3,3,I think they reflect my understanding well,Reflected moderately in the grading,Reflected moderately in the grading,Reflected moderately in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, experimenting with the code from class, watching videos that I find on my own" +4,3,I think they reflect my understanding well,Reflected moderately in the grading,Reflected moderately in the grading,Reflected moderately in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, download and run the notes, reading the documentation or course text" +3,3,I think they reflect my understanding well,Reflected strongly in the grading,Reflected moderately in the grading,Reflected strongly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, experimenting with the code from class, reading the documentation or course text, reading blogs or tutorials I find on my own, tinkering with code to answer other aspects of the material that I'm curious about, attended Dr. Brown's office hours" +3,3,I think they reflect my understanding well,Reflected moderately in the grading,Reflected moderately in the grading,Reflected moderately in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, download and run the notes, update the notes I took during class time, reading blogs or tutorials I find on my own, watching videos that I find on my own, tinkering with code to answer other aspects of the material that I'm curious about" +4,4,I think the achievements overestimate what I know (I know less than they reflect),Reflected moderately in the grading,Reflected moderately in the grading,Reflected moderately in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"download and run the notes, experimenting with the code from class, update the notes I took during class time, reading the documentation or course text, solving extra questions in the class notes, attended Beibhinn's office hours, attended Dr. Brown's office hours" +3,2,I think they reflect my understanding well,Reflected strongly in the grading,Reflected moderately in the grading,Reflected a little in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, experimenting with the code from class, reading the documentation or course text, watching videos that I find on my own, solving extra questions in the class notes, tinkering with code to answer other aspects of the material that I'm curious about" +5,4,I think they reflect my understanding well,Reflected strongly in the grading,Reflected strongly in the grading,Reflected perfectly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, update the notes I took during class time, attended Dr. Brown's office hours" +5,5,I think they reflect my understanding well,Reflected perfectly in the grading,Reflected perfectly in the grading,Reflected perfectly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, download and run the notes, experimenting with the code from class, update the notes I took during class time, reading the documentation or course text, reading blogs or tutorials I find on my own, watching videos that I find on my own, tinkering with code to answer other aspects of the material that I'm curious about, attended Beibhinn's office hours, attended Dr. Brown's office hours" +4,4,I think they reflect my understanding well,Reflected strongly in the grading,Reflected strongly in the grading,Reflected strongly in the grading,Is fairly reflected in the grading,Should be reflected more in the grading,Should be reflected more in the grading,"read the notes online, download and run the notes, experimenting with the code from class, reading the documentation or course text, reading blogs or tutorials I find on my own, attended Beibhinn's office hours, attended Dr. Brown's office hours" +5,4,I think they reflect my understanding well,Reflected strongly in the grading,Reflected strongly in the grading,Reflected strongly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Should be reflected more in the grading,"read the notes online, download and run the notes, experimenting with the code from class, reading the documentation or course text, solving extra questions in the class notes, tinkering with code to answer other aspects of the material that I'm curious about" +4,4,I think they reflect my understanding well,Reflected moderately in the grading,Reflected strongly in the grading,Reflected perfectly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, download and run the notes, experimenting with the code from class, update the notes I took during class time, reading the documentation or course text, reading blogs or tutorials I find on my own, watching videos that I find on my own, tinkering with code to answer other aspects of the material that I'm curious about" +5,4,I think they reflect my understanding well,Reflected strongly in the grading,Reflected strongly in the grading,Reflected strongly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, experimenting with the code from class, reading the documentation or course text, reading blogs or tutorials I find on my own, watching videos that I find on my own, tinkering with code to answer other aspects of the material that I'm curious about" \ No newline at end of file From f9fd2350c3e115a1900e86a3a06736874a7231b9 Mon Sep 17 00:00:00 2001 From: Sarah M Brown Date: Sun, 18 Oct 2020 15:30:02 -0400 Subject: [PATCH 8/9] remove erronesous add --- notes/data/feedback_structured.csv | 15 --------------- 1 file changed, 15 deletions(-) delete mode 100644 notes/data/feedback_structured.csv diff --git a/notes/data/feedback_structured.csv b/notes/data/feedback_structured.csv deleted file mode 100644 index 0b77eedd..00000000 --- a/notes/data/feedback_structured.csv +++ /dev/null @@ -1,15 +0,0 @@ -How much do you think you've learned so far this semester?,How much of the material that's been taught do you feel you understand?,How do you think the achievements you've earned so far align with your understanding?,Rank the following as what you feel the grading (when you do/not earn achievements) so far actually reflects about your performance in the class [How well I follow instructions],Rank the following as what you feel the grading (when you do/not earn achievements) so far actually reflects about your performance in the class [What I understand about the material],Rank the following as what you feel the grading (when you do/not earn achievements) so far actually reflects about your performance in the class [How much effort I put into assignments],How fair do you think the amount each of the following is reflected in the grading [How well I follow instructions],How fair do you think the amount each of the following is reflected in the grading [What I understand about the material],How fair do you think the amount each of the following is reflected in the grading [How much effort I put into assignments],Which of the following have you done to support your learning outside of class? -4,3,I think they reflect my understanding well,Reflected moderately in the grading,Reflected strongly in the grading,Reflected perfectly in the grading,Is fairly reflected in the grading,Should be reflected more in the grading,Should be reflected more in the grading,"read the notes online, download and run the notes" -4,4,I think the achievements underestimate what I know (I know more than they reflect),Reflected strongly in the grading,Reflected strongly in the grading,Reflected moderately in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Should be reflected more in the grading,"read the notes online, download and run the notes, reading the documentation or course text, reading blogs or tutorials I find on my own, watching videos that I find on my own, solving extra questions in the class notes, tinkering with code to answer other aspects of the material that I'm curious about" -3,3,I think they reflect my understanding well,Reflected moderately in the grading,Reflected moderately in the grading,Reflected moderately in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, experimenting with the code from class, watching videos that I find on my own" -4,3,I think they reflect my understanding well,Reflected moderately in the grading,Reflected moderately in the grading,Reflected moderately in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, download and run the notes, reading the documentation or course text" -3,3,I think they reflect my understanding well,Reflected strongly in the grading,Reflected moderately in the grading,Reflected strongly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, experimenting with the code from class, reading the documentation or course text, reading blogs or tutorials I find on my own, tinkering with code to answer other aspects of the material that I'm curious about, attended Dr. Brown's office hours" -3,3,I think they reflect my understanding well,Reflected moderately in the grading,Reflected moderately in the grading,Reflected moderately in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, download and run the notes, update the notes I took during class time, reading blogs or tutorials I find on my own, watching videos that I find on my own, tinkering with code to answer other aspects of the material that I'm curious about" -4,4,I think the achievements overestimate what I know (I know less than they reflect),Reflected moderately in the grading,Reflected moderately in the grading,Reflected moderately in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"download and run the notes, experimenting with the code from class, update the notes I took during class time, reading the documentation or course text, solving extra questions in the class notes, attended Beibhinn's office hours, attended Dr. Brown's office hours" -3,2,I think they reflect my understanding well,Reflected strongly in the grading,Reflected moderately in the grading,Reflected a little in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, experimenting with the code from class, reading the documentation or course text, watching videos that I find on my own, solving extra questions in the class notes, tinkering with code to answer other aspects of the material that I'm curious about" -5,4,I think they reflect my understanding well,Reflected strongly in the grading,Reflected strongly in the grading,Reflected perfectly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, update the notes I took during class time, attended Dr. Brown's office hours" -5,5,I think they reflect my understanding well,Reflected perfectly in the grading,Reflected perfectly in the grading,Reflected perfectly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, download and run the notes, experimenting with the code from class, update the notes I took during class time, reading the documentation or course text, reading blogs or tutorials I find on my own, watching videos that I find on my own, tinkering with code to answer other aspects of the material that I'm curious about, attended Beibhinn's office hours, attended Dr. Brown's office hours" -4,4,I think they reflect my understanding well,Reflected strongly in the grading,Reflected strongly in the grading,Reflected strongly in the grading,Is fairly reflected in the grading,Should be reflected more in the grading,Should be reflected more in the grading,"read the notes online, download and run the notes, experimenting with the code from class, reading the documentation or course text, reading blogs or tutorials I find on my own, attended Beibhinn's office hours, attended Dr. Brown's office hours" -5,4,I think they reflect my understanding well,Reflected strongly in the grading,Reflected strongly in the grading,Reflected strongly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Should be reflected more in the grading,"read the notes online, download and run the notes, experimenting with the code from class, reading the documentation or course text, solving extra questions in the class notes, tinkering with code to answer other aspects of the material that I'm curious about" -4,4,I think they reflect my understanding well,Reflected moderately in the grading,Reflected strongly in the grading,Reflected perfectly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, download and run the notes, experimenting with the code from class, update the notes I took during class time, reading the documentation or course text, reading blogs or tutorials I find on my own, watching videos that I find on my own, tinkering with code to answer other aspects of the material that I'm curious about" -5,4,I think they reflect my understanding well,Reflected strongly in the grading,Reflected strongly in the grading,Reflected strongly in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,Is fairly reflected in the grading,"read the notes online, experimenting with the code from class, reading the documentation or course text, reading blogs or tutorials I find on my own, watching videos that I find on my own, tinkering with code to answer other aspects of the material that I'm curious about" \ No newline at end of file From 70af4ec1ebcd170594d41446d61347777c3c0266 Mon Sep 17 00:00:00 2001 From: Sarah M Brown Date: Sun, 18 Oct 2020 17:42:01 -0400 Subject: [PATCH 9/9] link --- assignments/index.md | 1 + 1 file changed, 1 insertion(+) diff --git a/assignments/index.md b/assignments/index.md index 14b87150..45076531 100644 --- a/assignments/index.md +++ b/assignments/index.md @@ -8,3 +8,4 @@ Assignment TOC: - [Assignment 3](03-exploratory) Due September 29 - [Assignment 4](04-prepare) Due October 4 - [Assignment 5](05-construct) Due October 11 +- [Assignment 6](06-naive-bayes) Due October 20