I am a fast learner, reliable, and highly adaptable computer scientist with nearly 2 years of experience. I have an inquiring mind so, I love to learn new topics and technologies. I am interested in data heavy applications, data science as well as designing and analyzing new algorithms. I especially like working on NP problems that are featured in computer science literature. As a result of that, I love challenging myself by competing in programming contests.
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DataCamp | Credential |
---|---|
● Time Series With Python Track | c7fe632e98df1294490ab82e2f89dc3a4844f98b |
○ Time Series Analysis in Python | 30f4faf8dd831df2cecbe37e246c7b8164e0dbc8 |
○ Manipulating Time Series Data in Python | 073a158746f4ff2d182d29db3963aac5f6d4304e |
○ Visualizing Time Series Data in Python | 13055e33b84379e6dac1969792fe8ba282753e5a |
○ ARIMA Models in Python | c8e06caece4a18855f43714a3ef63d1b5727b5db |
○ Machine Learning for Time Series Data in Python | 9a1128f11df4125f8834051a9235056287bb7471 |
● Image Processing with Python Track | 4897bb90d5497a5e136b584156d3862e6d9ee828 |
○ Image Processing in Python | 932c84c999d36bc6cd5389fa5fca2422b8abaf5f |
○ Biomedical Image Analysis in Python | 4f46f5985cbaaef309937438320cdc8ab1bcc64b |
○ Image Processing with Keras in Python | ae00c2709858f3e2ae671d3f75417d6c1e0f4277 |
Udemy | Credential |
● Machine Learning A-Z™: Hands-On Python & R In Data Science | UC-6533048c-0058-4afe-bc96-8af7bf065e8a |
Coursera | Credential |
● Neural Networks and Deep Learning | MC9N39YP2QJR |
📃 Agglomeration-Based Node Importance Analysis in Wheel-Type Networks
📃 Introduction to Time Series Clustering