About the Website
- ✓ Image processing using Python libraries
- ✓ A step-by-step guide to materials data analysis via machine learning and deep learning
- ✓ Review of recent developments in the field of materials informatics
- I will share the codes developed by me and also provide tutorials on how to use publicly available open source codes related to multiscale materials design and informatics.
The Significance of Learning Data Analysis for Materials
Generally, most researchers (experimentalists) conduct innumerable experiments to reach the final target. In this process, we generate tons of data that involves enormous consumption of energy, resources, and, most importantly, time. The whole activity has a direct impact on our climate, too. Therefore, designing and performing relevant experiments by analyzing pre-existing data to predict new or improved materials via materials informatics and analytics is the need of the hour.
Click on blogs and tutorials to begin your adventure with materials data.
Latest Posts
- How to Code 2-Point Spatial Correlations for Materials Microstructures
- Exploring Hierarchical Materials
- How to Read Confusion Matrix for Multi-Class Classification
- How to Apply Ordinal Logistic Regression for prediction of Materials Properties March 2024
- How to Generate Hypothetical Dataset for Machine Learning
- How to Apply Binary Logistic Regression Analysis for Prediction of Materials Properties
September 2024
August 2024
April 2024
About the Author
I am Joyita Bhattacharya, PhD, a materials scientist and educator with expertise in microscopy, materials characterization, materials informatics, and machine learning. Through this website, I share tutorials, practical examples, and research-inspired articles that help students, researchers, and engineers apply modern data science techniques to real materials science problems.
Whether you are taking your first steps in materials informatics or looking to deepen your expertise, I hope these resources help you analyze data more effectively, interpret results with greater confidence, and discover new insights from materials datasets. Explore the tutorials to build practical skills, or browse the blog for applications, case studies, and discussions at the intersection of materials science, microscopy, and data analytics.
Here is the link to my LinkedIn profile.
bjoyita@gmail.com