Review machine learning and draft first-pass topics

[erictleung]

Below are some places to look at to see what kinds of topics should be covered. Comment below for what you think should be covered in the series of videos. Topics can range from simple to complex.

• [x] https://en.wikipedia.org/wiki/Machine_learning
  • Classification
  • Clustering
  • Regression
  • Anomaly detection
  • Association rules
  • Reinforcement learning
  • Structured prediction
  • Feature engineering
  • Feature learning
  • Online learning
  • Semi-supervised learning
  • Unsupervised learning
  • Learning to rank
  • Grammar induction
  • Neural networks (Autoencoder, Deep learning, multilayer perceptron, RNN, RBM, SOM, CNN)
• [ ] https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/index.htm
• [ ] https://medium.freecodecamp.com/every-single-machine-learning-course-on-the-internet-ranked-by-your-reviews-3c4a7b8026c0
• [ ] https://work.caltech.edu/telecourse.html
• [ ] https://github.com/dustinvtran/ml-videos
• [ ] https://github.com/ZuzooVn/machine-learning-for-software-engineers
• [ ] https://github.com/ujjwalkarn/Machine-Learning-Tutorials
• [ ] https://www.kaggle.com/wiki/Home
• [ ] http://www.learningmachines101.com/
• [ ] http://theconversation.com/what-is-machine-learning-76759
• [ ] https://github.com/metrofun/machine-learning-surveys
• [ ] A few useful things to know about machine learning
• [ ] NIPS 2016 - Look briefly of current topics being discussed
• [x] Top ten algorithms (https://www.quora.com/What-are-the-top-10-data-mining-or-machine-learning-algorithms)
  • C4.5
  • k-Means,
  • Support vector machine (SVM)
  • Apriori
  • Expectation maximization (EM)
  • PageRank
  • AdaBoost
  • k-Nearest Neighbors
  • Naive Bayes
  • Classification And Regression Trees (CART)
• [ ] Interactive machine learning intuition (http://www.r2d3.us/visual-intro-to-machine-learning-part-1/)
• [ ] https://unsupervisedmethods.com/over-150-of-the-best-machine-learning-nlp-and-python-tutorials-ive-found-ffce2939bd78
• [x] Introduction to Statistical Learning
  • Linear regression
  • Logistic regression
  • Linear discriminant analysis
  • Quadratic discriminant analysis
  • K-nearest neighbors
  • Cross-validation
  • Bootstrap resampling
  • Subset selection of models
  • Shrinkage methods of modeling (Ridge regression and Lasso)
  • Principal component regression
  • Partial least squares
  • Polynomial regression
  • Smoothing splines
  • Generalized additive models
  • Decision trees (regression and classification)
  • Bagging, random forests, and boosting
  • Support vector machines
  • Principal components analysis
  • K-means clustering
  • Hierarchical clustering

[satendrapalsingh]

Hi @erictleung! I'd like to contribute a few data-science video tutorials (on d3/data-viz and js/machine-learning) for freecodecamp's youtube channel. Right now I am working on visualizing FCC's 2017 code survey data with D3. Do you thing it's a good idea to build a set of hands-on D3 tutorials using this (real) project as a base? Or should I stick to the traditional tutorial format (list out D3js features, demonstrate each with a small example etc)?

[erictleung]

@satenndrra sorry for the late reply! Sure thing. I'll be changing the name of this repository to "data-science" or something to reflect its focus on data science, rather than just machine learning.

A practical hands on project might be a bit involved. Assuming nothing has changed, the videos are supposed to be quick videos people can view. I haven't seen the newest series of JavaScript videos on YouTube to see if they are similar or not.

I'd ask @QuincyLarson about having an involved hands-on tutorial for D3.js. I think it would great to maybe have an extended series for this hands-on tutorial. There are plenty of D3 blog tutorials, but such a static page to read a tutorial can be passive and not as engaging as a video can be.

[satendrapalsingh]

@erictleung ok, so if you are talking about the fcc-video-challenges format, I guess I can create a set of d3 concepts tutorials in that format - 2 minute videos, mostly whiteboard visuals and very little code/ syntax. I'll get back to you with a list of d3 topics/concepts breakdown that I can cover as video explanations.

And you're right, tutorials based on hands-on-projects would be very useful but very intensive - so this we could do later (if needed). I guess this would be more in line with the "Beau teaches JavaScript" set of videos on FCC/ Youtube channel.

Once the d3 part is done, I'd like to put something together for machine-learning. Will keep you updated.

[QuincyLarson]

@satenndrra @erictleung We are creating both YouTube videos and text-based guides for a wide variety of data science topics (and other technology topics). The best way to contribute at this point is to create Markdown-based tutorials and concept explanations. Then we can insert this into our forthcoming Guide structure. We'll formally announce and demo this as soon as it's ready, but you can go ahead and start on these guide articles.

[erictleung]

@QuincyLarson sweet, thanks! That's a natural place to start anyways for me to jot down notes.

[satendrapalsingh]

@QuincyLarson , @erictleung any guidelines for the text-based guides? Or any previous FCC guides you can point me to as an example.

[erictleung]

@satenndrra here are the current guides. I'll try to format mind similarly. Just make it Markdown compliant and have some YAML header with the title. I personally will try to keep my text 80 characters wide, but no need to do that yourself :smile:

I'll try to make some time this weekend to add stuff to this repository to start off the structure and give an example.

[QuincyLarson]

@satenndrra we are actively working on getting these contribution guides in place. In the meantime, I recommend preparing your guides in markdown and we can edit them and publish them once we get everything live. If you're looking for some ideas for topics to write about, check out https://github.com/freeCodeCamp/guide-articles/issues (we converted this from our old video challenge repo, and haven't fixed everything with it yet but we're working on it).

[QuincyLarson]

@erictleung would you be interested in creating issues for some of these on our new articles repo? https://github.com/freeCodeCamp/guide-articles/issues

[satendrapalsingh]

@erictleung, @QuincyLarson thanks! this helps :)