Abhinav Jha
Computer Science and AI taught interactively
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Private tutor - Abhinav Jha
Bachelors degree
/ 30 min
Abhinav - Know your tutor
From a young age, I have been deeply involved in technology and innovation. I earned a Bachelor's in Computer Science and Engineering and subsequently a Master's in Data Science and Analytics. My professional journey includes leading significant projects in AI and machine learning, developing solutions that have been adopted by top brands and achieved high accuracy in cybersecurity. I am currently pioneering a state-of-the-art fashion AI product at Angel Commerce Limited. My work not only involves technical development but also team leadership, mentoring a dynamic team to foster innovation. I am committed to applying my comprehensive skill set to drive forward the technological capabilities of organizations.
Abhinav graduated from D Y patil Institute of Engineering
Programming tutor specialities
Job readiness
Assignment help
Paired coding
Common Core State Standards - CCSS (USA)
GCSE (UK)
Debugging
Homework help
Upskilling
Exam prep
Programming class overview
In my data science and machine learning tutoring sessions, I provide comprehensive and detailed training tailored to both beginners and advanced students. My approach involves a balance of theoretical foundations and practical applications, using Python and relevant ML libraries. I assist students with assignments, project work, and preparation for exams. Feedback loops are integral to my methodology, ensuring that both I and my students continuously improve and that the sessions effectively meet their learning objectives.
Computer Science concept taught by Abhinav
The Tutor assisted the Student in setting up their coding environment to work on an assignment related to adversarial attacks. The Student downloaded the professor's code, installed necessary Python packages, and began to understand the structure of the provided neural network. The session concluded with a plan to continue running the code and debugging any issues in the next session.
Reproducibility with Random Seeds
Neural Networks and Hidden Layers
Fashion MNIST Dataset
CUDA and GPU Acceleration
Python Libraries (NumPy
Pandas
Torch)
Adversarial Attacks
An instructor guided a learner from Fort Lauderdale through building visualizations in PowerBI. The lesson focused on displaying average property median values by city, suburb, and postcode using hierarchies. They also worked on categorizing median values using formulas, encountering data type issues that required troubleshooting. The instructor will complete the categorization task and share the updated file, planning to review the completed work in a follow-up lesson.
PowerBI Data Hierarchy
Power Query for Data Type Conversion
Data Categorization in PowerBI
Abhinav Jha assisted Madison in debugging several code errors, including mismatched function names and attribute issues. They worked through output discrepancies, syntax errors, and incomplete code. Abhinav offered to review the code offline and schedule another session due to ongoing issues.
Code Correction and Iteration
Debugging Output Discrepancies
Addressing External Code Issues
Debugging 'add_owner' Attribute Error
Abhinav assisted Madison with debugging two Python coding problems from her assignment, focusing on correcting type errors and logical errors within class functions. They worked through issues related to data retrieval and manipulation. Due to time constraints, they scheduled another session to complete the remaining question, with Madison to provide her availability for scheduling.
Dictionary Iteration
Appending to a List
Using `len()`
Debugging 'int' object is not iterable
List Comprehension
Your programming tutor also teaches
Computer Science
Databases
Python
Web Development
Artificial Intelligence
Learner for programming class
Adult / Professional
School
College
All Levels
Teaching tools used by tutor
Xcode
Jupyter Notebook
Android Studio
Bitbucket
NetBeans
Dynamic programming classes
Pets are welcomed
Mobile joining
Note taking
Open Q&A
Parent feedback
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