ML for Hackers
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Machine learning and Data Science are cool, and really useful, but also they can be quite overwhelming when you are getting started, with complicated jargon and lots and lots of statistics and mathematical background. But, can we apply on it the long lasting Developer rule of “Hello world Now, Theory later”? In this talk I will share 5 tips from my journey becoming a Data Hacker, How the maker-mentality helped me become a better data-scientist, And how you can use your engineering strengths to become jack-of-all-trades Data Hacker.
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ML for Hackers
- 2. • Tech Lead at • recommendations and search group. • Maker & Hacker
- 12. Back-prop Regression Support vector Convoluted network Association learning Bayesian statistics Word2vec K-fold Chi- quare Dimension reduction Sensetivity Over Association learning True positive rate Data cleaning Deep-learning Dimension Feature ector Loss Regressor Random jungle poisso distribution MSE MaxEnt Markov Chain
- 16. The Hacker Way is an approach to building that involves continuous improvement and iteration. Hackers believe that something can always be better, and that nothing is ever complete. They just have to go fix it — often in the face of people who say it’s impossible or are content with the status quo. Mark Zuckerberg
- 42. Java Apache Mahout http://mahout.apache.org/ JavaML http://java-ml.sourceforge.net/ Jpmml https://github.com/jpmml Weka http://www.cs.waikato.ac.nz/ml/weka JS ml.Js https://github.com/mljs Classify https://github.com/harthur/classifier Brain https://github.com/harthur/brain .Net Accord framework http://accord-framework.net PMML Execution Engine https://syncfusion.com MicrosoftML https://github.com/Microsoft/microsoft-r/
- 47. start with the data 1
- 49. prepare the training set 2
- 50. Id:”641236288” Sin:00614950000P Name:”LEGO Batman Lunchset” Description:”The adventures of LEGO …” Price : 17.99 Rating: 3.4 Category:”Blocks” Availability: available Likes:394 Owns: 4055
- 53. Id:”641236288” Sin:00614950000P Name:”LEGO Batman Lunchset” Description:”The adventures of LEGO …” Price : 17.99 Rating: 3.4 Category:”Blocks” Availability: available Likes:394 Owns: 4055
- 54. Id:”641236288” Sin:00614950000P Name:”LEGO Batman Lunchset” Description:”The adventures of LEGO …” Price : 17.99 Rating: 3.4 Category:”Blocks” Availability: available Likes:394 Owns: 4055
- 57. Refrigerators Toys Shoes 1 0 0 1 0 0 0 1 0 0 0 1 Category Refrigerators Refrigerators Toys Shoes
- 60. Name ”Lego Star Wars Tie Fighter” ”Bosch Toaster” ”Star Wars Darth Vader Toaster”
- 61. Lego Star Wars Tie Fighter Bosch Toaster Darth Vader 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 0 0 0 1 1 1
- 62. vectorizer = TfidfVectorizer(stop_words='english', use_idf=False, min_df=5,max_df=0.75); nameVector = vectorizer.fit_transform( products['name'] )
- 66. Useful Lie
- 71. Profit 5
- 75. Test it 6
- 84. 1
- 88. 2
- 91. 3
Editor's Notes
- Machine learning Is a difficult topic to talk about. It’s a topic full of buzz
- I build shopping websites for a living And when starting to learn ML, I went into a major block.
- First theres the terminology. Lot’s of terminology you need to grasp before you can evne start writing code
- And then there the theoretical background. A lot if it With equation. An di failed in math.
- And that’s what’s today’s session is all about.
- And that’s what’s today’s session is all about. And here the definition is alittle different
- And this is exactly what we are going to do today.
- You might be joking here, but it’s actually a serious problem. Because if I can spate geeky products from non-geek products I can create better recommendations for my geek clients. And when you think a little deeper about it, it’s equivalent to questions like “what is a fashionable product” “what is an high quality product” “would a deal seeker like this product?”
- So.. What is a geeky product? Let’s do a little quiz?
- Batman statue is a geeky product. Ok so we've learned batman toys are geeky
- So we've learned toasters are not geeky. Unless they are darth vader toasters.
- Here it becomes tricky. But we alno know only true geeks will be caught with fitbit bands. Watches..
- So now when One approach is to get a specification from our product manager And translate it to a giant piece of code full of if\else. It doesn’t scale. Impossible to test. Impossible to debug, modify or change.
- or
- There is no shame in simple solutions Simple ML will take you a long way
- no reason It shouldn’t be be in your toolbox. As an engineer!
- no reason It shouldn’t be be in your toolbox. As an engineer!
- no reason It shouldn’t be be in your toolbox. As an engineer!
- no reason It shouldn’t be be in your toolbox. As an engineer!
- no reason It shouldn’t be be in your toolbox. As an engineer!