classify products into high-selling, low-selling and average-selling. This will aid in making decisions of which products to remain in the inventory. Once the analysis is complete, use the insights gained to make
Use these data analytics portfolio project ideas for beginners to build your own, and get some expert advice for your data portfolio in this guide.
Data Analysis Abid Ali AwanCertified data scientist, passionate about building ML apps, blogging on data science, and editing. Topics Data Analysis 25 Machine Learning Projects for All Levels 10 Data Visualization Project Ideas for All Levels Top 11 Data Mining Projects to Build Your Portfolio 60+...
making it ideal for data analysis, statistical modeling, and visualization. Renowned for its vast array of packages for statistical analysis, R is valued for conducting sophisticated statistical tests and exploratory data analysis.
3. What is Data Analysis, in brief? 4. How to know if a data model is performing well or not? 5. Explain Data Cleaning in brief. 6. What are some of the problems that a working Data Analyst might encounter? 7. What is Data Profiling? 8. What are the scenarios that could cause ...
Nov projects: The R-programming project for November is a sentiment analysis on song lyrics by different artists. There is lots of data wrangling involved to aggregate different lyrics, and compare the lyrics favored by 2 different artists. The code repository is added to theProjects page here....
To make any decision, big or small, you need the right data at your fingertips. You can dig a little deeper into your audience’s thoughts, ideas, and perspectives with qualitative data and see a much clearer picture. Whiledata analysis in qualitative researchcan be challenging, it is not ...
controlled experiments or architecture analysis (from Table 2 in [39]) are unsuited. Instead, we used anobservationalevaluation approach [39]. Subsequent versions of DAPS were applied in real data-analytics projects, which were done by students of professional and executive programs in data science...
In such projects, you would use APIs to get the actual data. Through data cleaning and analysis, you would get insights, which you could present in some nice visualizations. Finally, you could post it on reddit, get the feedback and potentially take them into account to improve your project...
The Quest for Artificial Intelligence: A History of Ideas and Achievements - Free Download Graph Algorithms for Data Science - Early Access Data Mesh in Action - Early Access Julia for Data Analysis - Early Access Casual Inference for Data Science - Early Access Regular Expression Puzzles and AI...