A collection of Data Science Interview Questions Solved in by Antonio Gulli

By Antonio Gulli

BigData and desktop studying in Python and Spark

Show description

Read or Download A collection of Data Science Interview Questions Solved in Python and Spark: Hands-on Big Data and Machine Learning PDF

Best introductory & beginning books

PHP 6/MYSQL programming for the absolute beginner

When you are new to programming with personal home page 6 and MySQL and are searhing for a superb advent, this is often the ebook for you. built via machine technological know-how teachers, books within the for absolutely the newbie™ sequence train the foundations of programming via easy online game production. you'll collect the abilities that you just desire for more effective programming purposes and should learn the way those talents should be placed to exploit in real-world eventualities.

Java Programming: From Problem Analysis to Program Design, 5th Edition

Designed for a primary machine technology (CS1) Java path, JAVA PROGRAMMING: FROM challenge research TO application layout 5e will encourage readers whereas construction a cornerstone for the pc technological know-how curriculum. With a spotlight on readers' studying, this article techniques programming utilizing the newest model of Java, and contains up-to-date programming workouts and courses.

Java For Testers Learn Java fundamentals fast

This ebook is for those that are looking to research Java. really humans on a workforce that are looking to study Java, yet who will not be going to be coding the most Java program i. e. Testers, Managers, company Analysts, entrance finish builders, Designers, and so on. for those who already recognize Java then this e-book is probably not for you.

Extra info for A collection of Data Science Interview Questions Solved in Python and Spark: Hands-on Big Data and Machine Learning

Sample text

Solution Code 51. What is a Gaussian Naïve Bayes? Solution 52. What is another way to use Naïve Bayes with continuous data? Solution 53. What is the Nearest Neighbor classification? Solution Code 54. What are Support Vector Machines (SVM)? Solution Code 55. What are SVM Kernel tricks? Solution 56. What is K-Means Clustering? Solution Code 57. Can you provide an example for Text Classification with Spark? Solution Code 58. Where to go from here Appendix A 59. Ultra-Quick introduction to Python 60.

Authorization_code for getting access. get_connections() print connections 28. Can you provide an example of connection to the Facebook API? com/docs/graph-api/overview and the following code fragment provides basic usage for getting friends’ connections with the user’s profile and for posting them on the Facebook wall. put_object("me", "feed", message="Posting in my wall") 29. What is a TFxIDF? Solution TFxIDF is a weighting technique frequently used for text classifications. The key intuition is to boost a term which is frequent for a document d in a collection of documents (Term Frequency=TF) but is not so frequent in all the remaining documents in (Inverse Document Frequency, IDF).

Solution In machine learning a set of true labels is called the gold set. This set of examples is typically built manually either by human experts or via crowdsourcing with tools like the Amazon Mechanical Turk[4] or via explicit/implicit feedback collected by users online. For instance: a gold set can contain news articles that are manually assigned to different categories by experts of the various subjects, or it might contain movies with associated rating provided by Netflix users, or ratings of images collected via crowdsourcing.

Download PDF sample

Rated 4.85 of 5 – based on 49 votes