Siddharth S.

I like solving challenging problems by leveraging my knowledge in machine learning, deep learning, computer science(data structures, algorithms, computer organization, and architecture), and software engineering or learning new stuff by conducting extensive research on topics related to problem and deliver product quality code written from scratch while leveraging any available open source. Strong understanding of core computer science fundamentals that govern the functioning of any computer/software system and a solid understanding of mathematics that serve as the foundation for ML/DL algorithms enables me to quickly pick up new programming languages, frameworks, and state-of-the-art ML/DL research literature for contributing to any software engineering or machine learning project significantly. Academically, I have completed masters in CSE with thesis in Machine Learning from Indian Institute of Science Bangalore and I have an in-depth understanding of major machine learning and deep learning algorithms along with underlying maths including but not limited to linear algebra, probability theory, and numerical optimization. Professionally I have worked for Platform Security Division at Intel as a software engineer, where I worked on security-related libraries/dll which enable software to leverage Intel ME and SGX for providing security on Intel hardware platforms with windows environment and also carried out various POCs in ML related product ideas. Following is an overview of my skills Machine Learning : SVM, Logistic Regression, Regression Analysis, Cluster Analysis, Naive Bayes, Ensemble Methods Deep Learning : RNN, CNN, GAN, Auto Encoders, Variational Auto-Encoder Computer Science : Data Structures and Algorithm, Computer Architecture and Organization, Operating System Math : Probability, Statistics, Linear Algebra, Unconstrained Numerical Optimization, Vector Calculus Backend: SpringBoot, AWS, MongoDB Platform: Android, Windows Language: C, C++, Python, C#, Java Tools: Matlab, Tensorflow