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Projects in Data Science
Today, the need for storing different types of data has become an essential requirement of any company whether it is big or small. Everyone wants to keep the records of their accounts, customers feedback, user details, a track of an employee and so on. This brings the concept of data science in the picture. They want to keep it easy, simple and hassle-free, and this is why understanding data science for the developers becomes important. Actually, data science can do a lot more than this and it can involve mathematics, chemometrics, computer science and other fields. Knowing this fact, we launched this course completely revolving around all the concepts and theories of applied data science.
Why should I choose this book?
Data science will soon be the option of choice in numerous public domains including health sector. To overcome this demand, the knowledge of applied data science will give you chance to fulfill all the requirements of your client. This course includes various topics covering all the aspects of data science making the concepts well-understood and well-versed for you.
What makes this book so valuable?
This course gives an insight into the basics of applied data science using Python covering topics like introduction to data science, setup, and extended data analysis such as dataset, analyzing output and others. Additionally, it also comprises of topics for making you understand linear and logistic regression. Furthermore, data visualization (MySQL, Plotly, Scattered plot, Advanced Scattered plot), time series, K-Means Clustering and decision tree are also explained.
This course includes
There is no such thing called right time, its you who make the time right! So, stop thinking and explore the concepts of Applied data science now!
1 | Introduction | ||
2 | Overview of Applied Data Science | ||
3 | Environmental setup - Jupyter Notebook |
4 | Understanding Problem Statement | ||
5 | About Dataset - Summary of Referees | ||
6 | Understanding the Dataset Dimension | ||
7 | Analysing the Output | ||
8 | Creating tidy tables | ||
9 | Analysing the Table Structure |
14 | Problem Statement- Data Visualization | ||
15 | MySQL Data | ||
16 | Plotly for Visualization | ||
17 | Database Connectivity and Configuration | ||
18 | Scattered Plot | ||
19 | Advanced Scattered Plot | ||
20 | Analysing Output |
21 | Activity for Extended Data Analysis | ||
22 | Plots of Data Analysis | ||
23 | Activity- Temperature Analysis | ||
24 | Performing Linear Regression | ||
25 | Activity Population Analysis |