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SALKIA BANDHAGHAT, Howrah Details verified of Ashutosh Pandey✕
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Thapar Institute of Engineering and Technology 2025
Master of Engineering - Master of Technology (M.E./M.Tech.)
SALKIA BANDHAGHAT, Howrah, India - 711106
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Class Location
Online class via Zoom
Student's Home
Tutor's Home
Years of Experience in Class 12 Tuition
1
Board
ISC/ICSE, CBSE
Preferred class strength
One on one/ Private Tutions, Group Classes
Subjects taught
English Literature, Computer Science, Physics, History, English, Geography
Taught in School or College
No
Class Location
Online class via Zoom
I am Willing to Travel
Tutor's Home
Years of Experience in Deep Learning Training
1
Deep_Learning_Techniques
Python, Tensorflow
Teaching Experience in detail in Deep Learning Training
My Deep Learning teaching experience focuses on bridging theoretical neural network mechanics with practical, first-principles code implementation in PyTorch and TensorFlow. As a university Teaching Assistant, I guide students through core concepts including feedforward architectures, backpropagation, CNN spatial feature extraction, and Transformer self-attention mechanisms while conducting live, line-by-line debugging of tensor shape mismatches, loss convergence issues, and dataloader pipelines. Whether explaining loss optimization or deploying computer vision models, my instruction equips learners to design, evaluate, and troubleshoot deep neural networks with total confidence.
Class Location
Online class via Zoom
Student's Home
Tutor's Home
Years of Experience in BTech Tuition
1
BTech Computer Science subjects
Natural Language Processing, Artificial Intelligence, Machine Learning, Machine Intelligence
BTech Branch
BTech Computer Science Engineering
Experience in School or College
My academic tutoring experience combines university-level lab instruction as a Teaching Assistant. In the college setting, I conduct lab sessions and doubt-clearing hours for undergraduate students across Python, Data Structures, Machine Learning, Deep Learning, and Image Processing, focusing on line-by-line live code debugging and evaluating assignment logic. On an individual level, I tutor school and undergraduate students in core programming (Python, C, CS Board Syllabus, and Mathematics) by breaking down complex algorithms from first principles and tailoring lesson plans directly to each student's specific learning gaps.
Type of class
Regular Classes
Class strength catered to
One on one/ Private Tutions, Group Classes
Taught in School or College
Yes
Teaching Experience in detail in BTech Tuition
My tutoring experience combines university-level lab instruction as a Teaching Assistant with personalized one-on-one private mentoring. In the college setting, I conduct lab sessions and doubt-clearing hours for undergraduate students across Python, Data Structures, Machine Learning, Deep Learning, and Image Processing, focusing on line-by-line live code debugging and evaluating assignment logic. On an individual level, I tutor school and undergraduate students in core programming (Python, C, CS Board Syllabus, and Mathematics) by breaking down complex algorithms from first principles and tailoring lesson plans directly to each student's specific learning gaps.
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Class Location
Online class via Zoom
Student's Home
Tutor's Home
Years of Experience in Class 12 Tuition
1
Board
ISC/ICSE, CBSE
Preferred class strength
One on one/ Private Tutions, Group Classes
Subjects taught
English Literature, Computer Science, Physics, History, English, Geography
Taught in School or College
No
Class Location
Online class via Zoom
I am Willing to Travel
Tutor's Home
Years of Experience in Deep Learning Training
1
Deep_Learning_Techniques
Python, Tensorflow
Teaching Experience in detail in Deep Learning Training
My Deep Learning teaching experience focuses on bridging theoretical neural network mechanics with practical, first-principles code implementation in PyTorch and TensorFlow. As a university Teaching Assistant, I guide students through core concepts including feedforward architectures, backpropagation, CNN spatial feature extraction, and Transformer self-attention mechanisms while conducting live, line-by-line debugging of tensor shape mismatches, loss convergence issues, and dataloader pipelines. Whether explaining loss optimization or deploying computer vision models, my instruction equips learners to design, evaluate, and troubleshoot deep neural networks with total confidence.
Class Location
Online class via Zoom
Student's Home
Tutor's Home
Years of Experience in BTech Tuition
1
BTech Computer Science subjects
Natural Language Processing, Artificial Intelligence, Machine Learning, Machine Intelligence
BTech Branch
BTech Computer Science Engineering
Experience in School or College
My academic tutoring experience combines university-level lab instruction as a Teaching Assistant. In the college setting, I conduct lab sessions and doubt-clearing hours for undergraduate students across Python, Data Structures, Machine Learning, Deep Learning, and Image Processing, focusing on line-by-line live code debugging and evaluating assignment logic. On an individual level, I tutor school and undergraduate students in core programming (Python, C, CS Board Syllabus, and Mathematics) by breaking down complex algorithms from first principles and tailoring lesson plans directly to each student's specific learning gaps.
Type of class
Regular Classes
Class strength catered to
One on one/ Private Tutions, Group Classes
Taught in School or College
Yes
Teaching Experience in detail in BTech Tuition
My tutoring experience combines university-level lab instruction as a Teaching Assistant with personalized one-on-one private mentoring. In the college setting, I conduct lab sessions and doubt-clearing hours for undergraduate students across Python, Data Structures, Machine Learning, Deep Learning, and Image Processing, focusing on line-by-line live code debugging and evaluating assignment logic. On an individual level, I tutor school and undergraduate students in core programming (Python, C, CS Board Syllabus, and Mathematics) by breaking down complex algorithms from first principles and tailoring lesson plans directly to each student's specific learning gaps.
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