Overview of the most interesting materials on data analysis and machine learning No. 4 (June 23 - July 7, 2014)
The previous issue of the review was entirely devoted to online courses on Data Science. This issue of the review of the most interesting materials on data analysis and machine learning will contain links to the latest materials on the topic. In this issue, some material focuses on the important topic of data visualization. There are several articles that describe small practical examples of data analysis. As usual, many articles are devoted to machine learning algorithms, including several articles devoted to the popular machine learning algorithms Deep Learning and Random Forest. There are also several links to interesting videos.
Data Analysis and Machine Learning Materials
- Visualization with D3.js [EN]
Some examples of data visualization with the D3.js library
- Data science, big data and statistics. Now, all together (Video Lecture) [EN]
Terry Speed, a distinguished professor from Berkeley, talks about combining traditional statistics with the science of data and big data.
- Top Data Analysts on Twitter [EN]
Microblogging of the best Data Analysts.
- Markov chains [EN]
Fundamentals of Markov chains in simple terms.
- Data Analysis Articles and Resources [EN] A
fresh list of interesting articles from leading data analysis experts.
- 25 Popular LinkedIn
Data Professionals [EN] List of 25 Popular Data Professionals and their LinkedIn Blogs.
- Visualization Techniques That You Know Since Your Childhood [EN]
An article about 6 simple but useful visualization principles.
- Watson and machine learning [EN]
Interesting article about the potential of the IBM Watson application in various areas of life.
- Why it's not so easy to become a Data Scientist [EN] This
article tries to explain that it is not enough to complete one or two online Machine Learning courses to be a Data Scientist.
- Deep Learning with Hadoop (Video Lecture) [EN]
Machine learning tools and technologies are constantly evolving. Deep Learning's machine learning technique is becoming increasingly popular. In this video, Josh Patterson and Adam Gibson discuss the parallelization capabilities of Deep Belief Networks in Deep Learning using the Hadoop YARN framework and Iterative Reduce library.
- Using the Facebook API with R [EN]
A small example of solving a practical problem using the Facebook social network and R.
- Books on data visualization [EN]
A large list of 35 books on data visualization.
- 12 interesting books and online resources on R [EN]
A list of 12 useful books and online resources for learning the programming language R.
- Product Deployment on R [EN]
Another article in a series of machine learning articles using the R programming language.
- Machine learning includes Kaggle competitions, too [EN]
An interesting answer to the article “Machine learning isn't Kaggle competitions” .
- Machine Learning Communities [EN]
A good article that provides a brief description of the current machine learning communities.
- Books on machine learning using R [EN]
A useful list of literature on machine learning using R.
- Is Data Scientist More than Data Analyst? [EN]
A small article comparing two concepts such as Data Scientist and Data Analyst
- The Basics of Data Analysis with Python [EN] This
article focuses on the first steps in data analysis with Pyhton and additional libraries.
- Cayley: An Open Graph Database [EN]
A short list of the benefits of an open source Cayley graph database.
- Probabilistic models: from naive Bayes to LDA, part 1 [RU]
Another article on the theoretical foundations of data analysis. In this case, we will talk about probabilistic models.
- List of open resources useful for machine learning. [EN]
An interesting set of links to free useful resources, as well as data sets for machine learning.
- Using Galene on LinkedIn [to EN]
The story of one of the leading engineers LinkedIn about how things have changed in the LinkedIn search architecture after the transition to the use of search Galene platform.
- Structured and Unstructured Data Types [EN]
A short article about the difference between structured and unstructured and melon types.
- Do I need a degree to be a Data Scientist? [EN]
Leading experts in data analysis to meet the interesting question of whether, and if necessary an academic degree to be a Data Scientist.
- Google I / O 2014 - Models of artificial intelligence based on biological models (Raymond Kurzweil) (Video lecture) [EN]
An interesting lecture on the topic of artificial intelligence from the famous scientist and futurist Ramond Kurzweil with Google I / O 2014.
- Cloud Storage Comparison 2014 [EN]
Fresh infographics compared to cloud storage.
- Domino - a modern platform for data analysis [EN]
A small article about the new flexible system for data analysis Domino.
- How to get started with machine learning [EN] A
great article on how a beginner can quickly get into the topic of machine learning and get started with real-world practical tasks.
- Image Clustering [EN]
Clustering similar images using MapReduce, with C # and R code examples.
- Analysis of posts on Google+ [EN]
A small example of the analysis of posts on Google+ using the programming language R.
- Comparison of SAS and Revolution R Enterprise performance [EN]
A small article on comparing SAS and Revolution R Enterprise performance from Revolution Analytics.
- Andrew Ng talks about Deep Learning [Video ]
Stanford University professor Andrew Ng talks about Deep Learning at a Paris machine learning meeting.
- Comparison of CART and Random Forest algorithms (Part 1) [EN]
The first part of the comparison of the popular CART (Classification and Regression Trees) and Random Forest algorithms.
- Comparison of CART and Random Forest algorithms (Part 2) [EN]
Continuation of comparison of machine learning algorithms CART (Classification and Regression Trees) and Random Forest.
- Comparison of In-Memory Database and In-Memory Data Grid [EN]
Comparison of two popular approaches to working with data.
- MongoDB in conjunction with the Google Cloud Platform [EN]
Brief article on working with MongoDB on the Google cloud platform (Google Cloud Platform).
- Generating and visualizing multidimensional random variables using R [EN]
A small code example for generating and visualizing multidimensional random variables in R.
- Data Shinobi 3 [EN]
Continuation of a series of articles on data analysis, the third part raises the issue of various directions in data analysis.
- Introduction to the Hadoop [to EN]
Another simple and brief description of the Hadoop.
- What is Deep Learning and why is there so much noise around this algorithm? [EN]
A short article on the popular Deep Learning machine learning algorithm suite.
Previous issue: Overview of the most interesting materials on data analysis and machine learning No. 3 (an overview of online courses)