Best products from r/Cloud
We found 2 comments on r/Cloud discussing the most recommended products. We ran sentiment analysis on each of these comments to determine how redditors feel about different products. We found 2 products and ranked them based on the amount of positive reactions they received. Here are the top 20.
1. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
- Language Published: English
- Binding: Hardcover
- Comes in Good condition
Features:
2. AmazonBasics USB 2.0 Extension Cable - A-Male to A-Female - 9.8 Feet (3 Meters)
- IN THE BOX: (1) 9.8 foot USB 2.0 A-Male to A-Female high-speed extension cable
- EXTENDS YOUR USB CONNECTION: Ideal extending your connection with printers, cameras, mice, keyboards and other USB computer peripherals
- GOLD-PLATED CONNECTORS: Constructed with corrosion-resistant, gold-plated connectors for optimal signal clarity and shielding to minimize interference
- CRYSTAL CLEAR SIGNAL: Features shielding that provides protection against noise from electromagnetic and radio-frequency signals, keeping your signal clear with less loss of bandwidth for higher performance
- COMPATIBILITY: Typically, the Male A connector plugs into your computer and the Female A connects to the cable you need extended; check your device manuals to make sure this is the connector you need
Features:
Machine learning isn't a cloud thing. You can do it on your own laptop, then work your way up to a desktop with a GPU, before needing to farm out your infrastructure.
If you're serious about machine learning, you're going to need to start by making sure your multivariate calculus and linear algebra is strong, as well as multivariate statistics (incl. Bayes' theorem). Machine learning is a graduate-level computer science topic, because it has these heady prerequisites.
Once you have these prereqs covered, you're ready to get started. Grab a book or online course (see links below) and learn about basic methods such as linear regression, decision trees, or K-nearest neighbor. And once you understand how it works, implement it in your favorite language. This is a great way to learn exactly what ML is about, how it works, how to tweak it to fit your use case.
There's plenty of data sets available online for free, grab one that interests you, and try to use it to make some predictions. In my class, we did the "Netflix Prize" challenge, using 100MM Netflix ratings of 20K different movies to try and predict what people like to watch. Was lots of fun coming up with an algorithm that wrote its own movie: it picked the stars, the genre and we even added on a Markov chain title generator.
Another way to learn is to grab a whitepaper on a machine learning method and implement it yourself, though that's probably best to do after you've covered all of the above.
Book: http://www-bcf.usc.edu/~gareth/ISL/
Coursera: https://www.coursera.org/learn/machine-learning
Note: this coursera is a bit light on statistical methods, you might want to beef up with a book like this one.
Hope this helps!
It makes me cringe seeing them try to hold a laptop up to the wall. One of these would help.
http://www.amazon.com/AmazonBasics-Extension-Cable--Male--Female/dp/B001TH7GUU/ref=sr_1_1?ie=UTF8&qid=1426389038&sr=8-1&keywords=amazon+usb+extension