stani.ca
Blog | Stani.ca
http://stani.ca/blog
Game development, UI/UX design, machine learning, gaming and other cool links. 24 January, 2016. 19 January, 2016. Love it or hate it, Vim is an extremely useful tool. This. Is a great tutorial that covers the basics and advanced techniques. Top 30 Books Linked on Hacker News. 18 January, 2016. Scraped Hacker News comments for Amazon links and visualized the top 30 referenced books. I’ve read 4 of these books and have my eye on a few more I’m going to read next. Here’s a PDF link. 11 January, 2016. Expla...
relegant.com
Software Engineering : Relegant Index
http://www.relegant.com/software-eng
Skip to main content. Skip to search forms. Geek Time with Josh Bloch. How to Design a Good API. Best Practices in JavaScript Library Design. By John Resig (author of jQuery). Open source library from Google. Applied Computer Science Lab. Bertrand Meyer, Dec. 8, 2003. Diving for Perls - the poetry of programming. Elegance and Other Design Ideals. Bjarne Stroustrup, Feb. 23, 2004. Eric Gamma on Flexibility and Reuse. May 30, 2005. Forget Technical Debt - Here's How to Build Technical Wealth.
reudismam.wordpress.com
Machine Learning Books | Software Engineering Data Science
https://reudismam.wordpress.com/2014/05/05/machile_learning_books
Software Engineering Data Science. On May 5, 2014. In this post we list a set of books that can be useful to the student learning machine learning. A Course in Machine Learning. A Course in Machine Learning is a set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.). Its focus is on broad applications with a rigorous backbone (Hal Daumé III, 2012). These are t...
reudismam.wordpress.com
reudismam | Software Engineering Data Science
https://reudismam.wordpress.com/author/reudismam
Software Engineering Data Science. On May 14, 2014. Software is present on every activity nowadays; it is on our homes, car, mobile phones, etc. An interesting aspect is that software invariably evolves. In this post we discuss some features related to Software Evolution. Dimensions of Software Evolution. In accordance with (Mens and Demeyer, 2008), the software evolution types can be classified in:. Is any modification of a software product after delivery to improve performance or maintainability;.
advanceddataanalytics.net
eBooks | Data Analytics & R
https://advanceddataanalytics.net/ebooks
What is …. Data Analytics and R. Please check licensing before downloading documents using the below listed links and note, that the validity of links might change quickly. A Beginner’s Guide to R. A Brief Introduction to Neural Networks. A Computational Approach to Statistics. A Course in Machine Learning. A Course in Machine Learning. A Course in Machine Learning. A Course in Time Series Analysis. A Field Guide to Genetic Programming. A First Course in Design and Analysis of Experiments. A Trio of Texts.
nlpers.blogspot.com
natural language processing blog: 2014/10
http://nlpers.blogspot.com/2014_10_01_archive.html
Natural language processing blog. My biased thoughts on the fields of natural language processing (NLP), computational linguistics (CL) and related topics (machine learning, math, funding, etc.). Hyperparameter search, Bayesian optimization and related topics. In terms of (importance divided-by glamour), hyperparameter (HP) search is probably pretty close to the top. We all hate finding hyperparameters. Default settings are usually good, but you're always left wondering: could I have done better? A facul...
nlpers.blogspot.com
natural language processing blog: Machine learning is the new algorithms
http://nlpers.blogspot.com/2014/10/machine-learning-is-new-algorithms.html
Natural language processing blog. My biased thoughts on the fields of natural language processing (NLP), computational linguistics (CL) and related topics (machine learning, math, funding, etc.). Machine learning is the new algorithms. Fast forward N years. My claim today- -and I'm speaking really as an NLP person, which is how I self-identify- -is that machine learning is the new core. Everything that algorithms was to computer science 15 years ago, machine learning is today. All of my experience in the...
jeffchang001.blogspot.com
Jeff Chang's Blog: Big Data Books
http://jeffchang001.blogspot.com/2014/07/big-data-books.html
Jul 12, 2014. An Introduction to Statistical Learning with Applications in R. The Elements of Statistical Learning. A Programmer’s Guide to Data Mining. Probabilistic Programming and Bayesian Methods for Hackers. Think Bayes, Bayesian Statistics Made Simple. Data Mining and Analysis, Fundamental Concepts and Algorithms. An Introduction to Data Science. Machine Learning – The Complete Guide. Bayesian Reasoning and Machine Learning. A Course in Machine Learning. Subscribe to: Post Comments (Atom).
wa2014.stei.itb.ac.id
Uncategorized | Blog Waskita
http://wa2014.stei.itb.ac.id/category/uncategorized
Menurut grafik di bawah ini, jika kita kerja lebih dari 40 jam seminggu maka produktivitas kita akan meningkat (misal 60 jam seminggu). Namun produktivitas ini tidak akan bertahan lama, dan perlahan-lahan akan menurun di bawah produktivitas jika kita kerja 40 jam seminggu. Http:/ www.lostgarden.com/2008/09/rules-of-productivity-presentation.html. Beberapa bacaan yang juga terkait:. Http:/ blog.bufferapp.com/optimal-work-time-how-long-should-we-work-every-day-the-science-of-mental-strength. Berikut ini tu...
datascienceacademy.com
Free Data Science Courses | Data Science Academy
http://datascienceacademy.com/free-data-science-courses
Big Data Science Courses. Free Data Science Courses. Free Data Science Courses. The Little List of Free #DataScience Courses. Free Online Data Science Courses and Data Science Training. Click on the free data science courses links below:. The Open Source Data Science Masters. Harvard CS109 Data Science. Introduction to Data Science by Jeff Hammerbacher at UC, Berkeley. Introduction to Data Science @coursera. Introduction to Data Science @UofWashington. Data Science Course @ColumbiaUni notes by @mathbabe.
