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Hands-On Fundamentals of Data Science with Go [Video]

More Information
Learn
  • Perform data collection and use statistical models to perform data visualization in Go.
  • Clean and filter data for data formatting.
  • Implement models like Naïve Bayes to work efficiently with high speed in Go.
  • Build an end-to-end model like Regression to analyze new data.
  • Solving predictive analytics through decision trees model.
  • Practical coverage on how to build data science pipeline in Go
  • Explore how Go code differs with Python
About

Go (also known as Golang), created at Google, is increasingly proving to be faster, easy to code in, highly efficient and concurrent programming languages. It is the next-gen language of data science, machine learning and AI in general - as it strikes a great balance between productivity and maintainability of code. Many data scientists prototype models, which are then deployed to production by someone else, Go will allow you to do both! In these videos, you will get complete hands-on guidance on how to perform data mining, natural language processing, machine learning, linear algebra and understand in detail how you can use these to boost data science projects in your teams using Go. You will gain practical coverage on how to do data collection, data cleaning and mining, use of statistical models for analysis and data visualization. You will also get to use cutting-edge libraries in Go, and use them with popular datasets used by the machine learning community. The course would also guides you to build real-life hands on projects like twitter bot which tweets on your behalf, sentiment analysis on movie reviews using Naïve Bayes and decision trees, two different kinds of recommendation systems to recommend movies and a regression model to perform stock prices forecasting, along with performing your own data visualizations in Go.

You will get a complete hold on the use of statistics, linear algebra and understand in detail how you can boost your data science using Go. You will gain practical coverage on how to do data collection, data sanitation and munging, the use of statistical models for analysis and data visualization. The video would also get you couple with the fundamentals of machine learning along with a quick run through in implementing models such as Decision Trees, Naive Bayes, SVM and so on. You will also get to know how you can work with big data processing tools like Apache Spark and Kafka in your data science projects. The course would also get you through a couple of examples like recommendation system, sentimental analysis and stock prices forecasting.

The code bundle for this video course is available at https://github.com/PacktPublishing/Hands-on-Fundamentals-of-Data-Science-with-Go

Style and Approach

This video course will take a practical approach and cover data science concepts in Go. There will be examples to implement and bring together all the material learned. The entire Go code will be walked through in detail along with the use of popular datasets used by the machine learning community.

Features
  • Get practical coverage on entire data science life cycle with Go
  • Build several real-life projects to expand your data science portfolio in Go
  • Numerous examples with ready tips and tricks for your ongoing data science projects
Course Length 1 hour 47 minutes
ISBN 9781789539103
Date Of Publication 30 Dec 2018

Authors

Sanket Gupta

Sanket Gupta is a New York based Engineer who has experience of working on various data science projects in several languages like Go and Python. He is an active contributor to the data science community and his blogs have been featured on various publications. He is passionate about teaching and educating in the area of data science. He enjoys travelling, reading astronomy books and listening to classic rock.