Divya Darapuneni Deep learning Research and development
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With 2.9 years of real-time experience in Machine Learning and Deep Learning and with passion and 1 year expertise in teaching, completing the student phase I am confident in my ability to effectively teach the following skills to my students understanding what they were expecting as i did in my student phase :

Domains:
I can teach excellently Formal language and automata theory and assure my students with easy understanding.
Machine Learning with Python: Comprehensive understanding and practical experience in applying machine learning techniques using Python.
Deep Learning with Python: Proficient in developing and implementing deep learning models using Python, including a clear explanation of the models(like diffusion models, GAN's, RNN's,Transformers, etc) with accompanying code.
Data Structures and Algorithms in C: Expertise in teaching all data structures and algorithms, with real-time coding examples in C.
pandas .
Programming Languages:
Complete Python Programming: Extensive experience in Python programming, covering all essential concepts and applications.
Java Programming: Solid understanding of Java programming, including object-oriented principles and application development.
C Programming: Strong foundation in C programming, focusing on system-level programming and performance-critical applications.
I am dedicated to providing my students with a thorough understanding of these domains and programming languages, ensuring they are well-equipped to succeed in their academic and professional endeavors.

Subjects

  • Software Engineering Grade 10-Masters/Postgraduate

  • Deep Learning Beginner-Expert

  • Data Structures and Algorithms in C Beginner-Expert

  • Formal Languages and Automata Theory Beginner-Intermediate

  • DBMS SQL Beginner-Expert

  • Python Programming Course Grade 7-Bachelors/Undergraduate

Experience

  • Deep learning Research and development Engineer (Nov, 2022–Present) at Boltzmann Labs
    Working as part of an AI based small molecule discovery product.
    Developed few generative models for hit generation using(GAN's,RNN,diffusion models,Transformers). These model's explores the chemical space of reference input set iteratively and generates similar sets with better properties as specified.
    Developed an Active Learning cycle for building an inhouse activity models and providing guidance for Developing few other features that help in Drug Discovery cycle with AI.
    developed machine learning based pipeline for building models for different use cases.

Education

  • BE/B.Tech/BS (Oct, 2022–May, 2023) from AP IIIT NUZVID
  • BE/B.Tech/BS (May, 2019–May, 2023) from AP IIIT NUZVID–scored 9.04 cgpa

Fee details

    ₹300–700/hour (US$3.57–8.32/hour)

    Data structures and algortihms (min - 800 max - 1000)
    Machine learning (min - 900 max - 1000)
    Deep learning (min - 900 max - 1000)
    python or java programming (min - 500 max - 700)
    formal languages and automata theory /DBMS with SQL (min - 700 max - 900)

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