Supercharge Scientific Computing in Python with Numba
Talk
Go to NumFOCUS academy page.
Python is the goto language for computational research, but often we are hit by the performance bottleneck of this language. In this talk, we will delve into 3 real-world computational exercises to introduce the core concepts, ease & effectiveness of using Numba, a JIT compiler that translates Python & NumPy code into fast machine code. Let’s supercharge our scientific computing research today!
Speaker
Ankit Mahato
A die hard Pythonista, Ankit is an open source contributor and a former Google Summer of Code scholar under Python Software Foundation. Currently, he is working in the domain of scientific computing and Machine Learning in IoT devices.
Ankit has 6 years of industrial experience (Associate - JP Morgan, Data Scientist & Product Manager - Fuzzy Logix, USA) in machine learning, quantitative modelling, data analytics and visualization. Over the years, he has developed an expertise in handling the entire data analytics pipeline comprising – ingestion, exploration, transformation, modeling and deployment. He is a polyglot programmer with an extensive knowledge of algorithms, statistics and parallel programming. He has shipped multiple releases of DB Lytix, a comprehensive library of over 800 mathematical and statistical functions used widely in data mining, machine learning and analytics applications, including “big data analytics”.
An IIT Kanpur alumnus, Ankit is also an active researcher with publications on scientific computing in international journal and conferences. He is actively working in the domain of Analytics and has presented his work in:
- PyCon India 2019 (Talk)
- 5th International Conference on Data Science and Engineering 2019
- Data Science Congress 2018
- 5th IIMA International Conference on Advanced Data Analysis, Business Analytics and Intelligence 2017
- SciPy India 2017 (Talk)
He is also an active contributor to the Indian Python Community and has conducted 5 workshops in PyCon India 2017 & 2019 and Scipy India 2017, 2018 & 2019.