Overview of the most interesting materials on data analysis and machine learning No. 8 (August 4 - 11, 2014)
I present to you the next issue of a review of the most interesting materials on the topic of data analysis and machine learning. There are many practical examples of code in the programming languages R and Python in this release. Also in this review there are a lot of articles that will be of interest to beginners. Several articles focus on online courses. As usual, a lot of material is devoted to machine learning algorithms.
Data Analysis and Machine Learning Materials
- Introduction to Machine Learning
An excellent article describing the basic concepts of machine learning.
- Linear classification in R
Three types of linear classification with examples in the programming language R.
- Spotify recommendations using Deep Learning
The author describes how the recommendation system works in the popular Spotify service.
- The new online course on artificial intelligence
A rather interesting description of the new online course on artificial intelligence from LIRIS called IDEAL MOOC starts in October 2014.
- One year of participation in Kaggle competitions
In this article, the author talks about the experience of his participation in various machine learning competitions at Kaggle in one year. Prior to this, the author did not have much experience on the subject of machine learning.
- Learning from the best
An extremely useful publication that contains tips from the best Kaggle members on how to succeed in machine learning competitions.
- Inserting NA values into arbitrary places in a vector
An example of useful code in the programming language R. In this code example, we often solve the problem when, for various purposes, several NA values must be inserted into arbitrary places in a value vector.
- New data analysis channel on YouTube
The author of the Oz Analytics blog, in addition to his blog, has opened a new channel on YouTube, which will cover various topics related to analytics, business analytics and Data Science.
- Visualization of Markov chains
Excellent visualization of the Markov chain algorithm.
- Visualizing geographic data with R
An interesting article on how to visualize geographic data using the R programming language and the popular visualization library ggplot2.
- Operation chains: an interesting feature in the dplyr library An
interesting example of the code for using operation chains when using the popular dplyr library for the programming language R.
- Certificates and certification in the field of data analysis
A large interesting list of possible course options, at the end of which you can get a certificate in the field of data analysis. There are options for online courses, various certification options, and full-time studies.
- Successful application of the predictive model
A useful post from the author of MachineLearningMachinery on how to find interesting and successful applications of the predictive model.
- What skills are important for Data Scientist
A very interesting article is about which skills are important for a novice data analyst, and which are not as important as it might seem at first glance for your portfolio.
- NoSQL or SQL: how to make the right choice?
In recent years, the number of different database options that you can choose for your application has grown significantly. Because of this, application developers had a lot of questions, this webcast will try to answer the most important of them.
- Microsoft's plans for machine learning This
article talks about Microsoft's plans for the future in machine learning. Microsoft is launching its cloud-based Azure ML platform, which has received much attention in this publication.
- How to become a Data Scientist: MS Program, Bootcamp or MOOC
Interesting discussions about what paths exist to become a Data Scientist and what each path has features.
- Higgs Boson Machine Learning Competition Solution at Kaggle
An option to solve the Higgs Boson Machine Learning Competition solution at Kaggle. The author uses Python, Pandas and Scikit Learn for his solution.
- Comparison of the life expectancy of women and men
A good example of data processing in the programming language R.
- Heiko Strathmann talks about the Shogun machine learning library
Heiko Strathmann in this short video lecture talks about the Shogun machine learning library, of which he is one of the authors. The main direction of this library is the use of the support vector method to solve the problems of regression analysis and classification.
- Air crash
data processing A good example of data processing in the programming language R.
- Parametrized SQL queries
A good article on how to write and use parameterized SQL queries, including how to use them in the programming language R.
- Digest of the best resources from DataScienceCentral (August 4)
A good list of fresh interesting articles and resources from DataScienceCentral.
- The Seven Pillars of Statistical Wisdom
A short article about 7 things that are extremely important in statistical science.
- Bad habits when writing SQL code A
good article with a small list of errors that are often made when writing SQL code.
- An example of using the glm () function in R
A simple example of using the glm () function in the R programming language from the stats library.
- Preparing data for predictive modeling
An interesting article from the author of MachineLearningMachinery about the possibilities of improving the predictive model due to better data preprocessing.
- 11 Essentials for Data Science
An excellent 11-point cheat sheet from the DataScienceCentral portal, which will be useful to anyone interested in the Data Science theme.
- Interesting ideas from biostatistics for A / B testing
This material may attract the attention of those who are interested in the topic of A / B testing. This short article offers some ideas from biostatistics that can be applied for A / B testing.
- Machine Learning and Computer Vision
Another article from the Microsoft Technet Machine Learning Blog devoted to the use of machine learning in solving image recognition issues and the use of computer vision technologies. The article is small and written in simple language, without diving into the details of this rather complex topic.
Previous issue: Overview of the most interesting materials on data analysis and machine learning No. 7 (July 28 - August 4, 2014)