N. Z. Tsaku and S. Kosaraju, " Boosting Recommendation Systems through an Offline Machine Learning Evaluation Approach," ACM Southeast Conference (ACM-SE 2019), Accepted
S. Kosaraju, M. Masum, N. Tsaku, P. Patel, T. Bayramoglu, G. Modgil, and M. Kang†, "DoT-Net: Document Layout Classification Using Texture-based CNN", The 15th International Conference on Document Analysis and Recognition (ICDAR), 2019. Accepted
S. Kosaraju, N. Z. Tsaku, P. Patel, T. Bayramoglu, G. Modgil, and M. Kang†, "Table of Contents Recognition in OCR Documents Using Image-based Machine Learning," ACM Southeast Conference (ACM-SE 2019), Accepted
10 core machine learning topics and 6 projects completed during my sojourn at Udacity.
Core Curriculum
Machine Learning
Concepts of Machine Learning
Supervised Learning
Deep Learning
Unsupervised Learning
Data Science
Software Engineering
Writing Data Science blog posts, leveraging GitHub
Data Engineering
Experimental design and recommendations
Completed Projects
1. Finding Donors for charity Machine Learning (CharityML)
2. Cross Industry Standard Processing of Data Mining (CRISP-DM) model applied on Seatle Airbnb to enhance insightful decision making. Github
2. Creating an Image classifier. Medium
3. Identifying Customer Segments with Arvato. Medium
4. Disaster Response Pipelines. Github
5. Recommendations with IBM. Github1 Github2
6. Customer Segments with Arvato: Ideation architecture and implementation. Medium