This is the code repository for Hands-On Fundamentals of Data Science with Go [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Go (also known as Golang) is risingly proving to be faster execution, ease of codes and one of high efficiency programming language. With Data science domain being cumbersome with lots of data, data scientist and data engineers can take full advantage of Go's attributes and accomplish 90 percent of data science tasks faster and with high efficiency. You will get 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, 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. The course would also get you through 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
- 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.
To fully benefit from the coverage included in this course, you will need:
This video is for Go programmers who wants to enter data science OR a data analyst, data engineer, data scientist who wants to make use of Go in their data science projects. You need to have basic familiarity with Go and essentials of linear algebra to take full benefit of this video.
This course has the following software requirements:
Chrome or any Browser