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Python Training classes > Python Training in Lucknow > Python Training in Indira Nagar > Nitesh Kumar Sharma

Nitesh Kumar Sharma Python trainer in Lucknow

Nitesh Kumar Sharma

(18)
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(18)
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locationImg Indira Nagar, Lucknow
2 yrs of Exp
students 32 students
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Details verified of Nitesh Kumar Sharma✕

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Education

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Identity is verified based on matching the details uploaded by the Tutor with government databases.

Python Expert | Django | Machine Learning | Deep Learning | Data Science

Online Classes
Student's home
I am a Python Expert, Django Web Development, Machine Learning, Deep Learning, Data Science Trainer.

I was giving online training for the last 2 years. Currently, I am working in TCS and as part-time I provide Corporate training.

I have completed my Bachelor of Technology in Computer Science & Engineering domain with Honors.

My key skills are:
* Python Programming
* Django (Web Development)
* Machine Learning
* Deep Learning
* Data Science.

Beyond that, I helped many M.Tech and Ph.D. students in their research work and thesis work.
Priyanka

He is best tutor! .He was great explaining everything.The lesson arrangement was very interesting and useful. A great tool you don't want to miss!.He is great gaps in student's knowledge and working systematically to filling them. Thank you sir.

Languages Spoken

Hindi Mother Tongue (Native)

English Proficient

Education

Dr. A. P. J. Abdul Kalam Technical University Lucknow 2019

Bachelor of Technology (B.Tech.)

Address

Indira Nagar, Lucknow, India - 226016

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Teaches

Python Training classes
17 reviews

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Python Training classes

2

Course Duration provided

6-12 months, 3-6 months, 1-3 months

Seeker background catered to

Educational Institution, Individual, Corporate company

Certification provided

No

Python applications taught

Data Science with Python, Regular Expressions with Python , Text Processing with Python, Data Visualization with Python, Automation with Python , Data Extraction with Python , Web Development with Python , Data Analysis with Python , Web Scraping with Python , GUI (Graphical User Interfaces) with Python , Scipy Stack with Python , Help in assignment, Machine Learning with Python

Teaching Experience in detail in Python Training classes

I had worked in TCS after that I started to share my knowledge by providing the training as my part-time. I have provided training in Python, Django, Machine Learning, Deep Learning, Data Science more than 150+ Engineering colleges, and online students.

Deep Learning Training

Class Location

Online class via Zoom

I am Willing to Travel

Tutor's Home

Years of Experience in Deep Learning Training

2

Deep_Learning_Techniques

Tensorflow, Python

Data Science Classes
1 review

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Data Science Classes

2

Data science techniques

Python, Machine learning, Artificial Intelligence

Reviews

4.7 out of 5 18 reviews

Nitesh Kumar Sharma https://p.urbanpro.com/tv-prod/auth/photo/9247543-small.png Indira Nagar
4.70518
Nitesh Kumar Sharma
P

Python Training

"He is best tutor! .He was great explaining everything.The lesson arrangement was very interesting and useful. A great tool you don't want to miss!.He is great gaps in student's knowledge and working systematically to filling them. Thank you sir. "

Nitesh Kumar Sharma
A

Python Training

"A really good experience in python training classes and all the queries are clearly related in python. "

Nitesh Kumar Sharma
A

Python Training

"He is best trainer. Very helpful and supportive teacher. Detailed explanation and clarity of topics are provided. "

Nitesh Kumar Sharma
M

Python Training

"Good and knowledgeable trainer with friendly nature. I have done python course from CETPA Lucknow under his guidance and overall experience great from Learning Basic Python to do projects. "

Contact

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Have you attended any class with Nitesh?

Answers by Nitesh

Answered on 19/10/2023

Ask a Question

Post a Lesson

What is the role of data visualization in data science?

Data visualization in data science serves as a visual storyteller, simplifying complex data into easy-to-understand charts and graphs. It helps analysts and decision-makers spot patterns, draw insights, and communicate findings effectively.
Answers 2 Comments
Dislike Bookmark

Answered on 19/10/2023

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Post a Lesson

How can you handle categorical data in machine learning models?

To handle categorical data in machine learning, you can use techniques like one-hot encoding, where each category becomes a binary feature, or label encoding, which assigns a unique number to each category. These transformations allow machine learning models to work with categorical data effectively. ...more

To handle categorical data in machine learning, you can use techniques like one-hot encoding, where each category becomes a binary feature, or label encoding, which assigns a unique number to each category. These transformations allow machine learning models to work with categorical data effectively.

Answers 1 Comments
Dislike Bookmark

Answered on 19/10/2023

Ask a Question

Post a Lesson

What is the bias-variance decomposition of mean squared error?

The bias-variance decomposition of mean squared error explains how prediction errors can be broken into three parts: bias (systematic errors), variance (fluctuations), and irreducible error (noise). It helps understand how model complexity affects overall prediction accuracy.
Answers 2 Comments
Dislike Bookmark

Answered on 19/10/2023

Ask a Question

Post a Lesson

What is the difference between supervised and semi-supervised learning?

Supervised learning uses labeled data (input-output pairs) to train a model, while semi-supervised learning uses a combination of labeled and unlabeled data, often improving performance by leveraging both types of information. It's like having some answers and trying to find more by using clues from... ...more

Supervised learning uses labeled data (input-output pairs) to train a model, while semi-supervised learning uses a combination of labeled and unlabeled data, often improving performance by leveraging both types of information. It's like having some answers and trying to find more by using clues from the questions you don't know.

Answers 1 Comments
Dislike Bookmark

Answered on 19/10/2023

Ask a Question

Post a Lesson

What are some popular deep learning frameworks?

Some popular deep learning frameworks are TensorFlow and PyTorch, which provide tools to build, train, and deploy deep neural networks for various tasks like image recognition and natural language processing.
Answers 3 Comments
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Teaches

Python Training classes
17 reviews

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Python Training classes

2

Course Duration provided

6-12 months, 3-6 months, 1-3 months

Seeker background catered to

Educational Institution, Individual, Corporate company

Certification provided

No

Python applications taught

Data Science with Python, Regular Expressions with Python , Text Processing with Python, Data Visualization with Python, Automation with Python , Data Extraction with Python , Web Development with Python , Data Analysis with Python , Web Scraping with Python , GUI (Graphical User Interfaces) with Python , Scipy Stack with Python , Help in assignment, Machine Learning with Python

Teaching Experience in detail in Python Training classes

I had worked in TCS after that I started to share my knowledge by providing the training as my part-time. I have provided training in Python, Django, Machine Learning, Deep Learning, Data Science more than 150+ Engineering colleges, and online students.

Deep Learning Training

Class Location

Online class via Zoom

I am Willing to Travel

Tutor's Home

Years of Experience in Deep Learning Training

2

Deep_Learning_Techniques

Tensorflow, Python

Data Science Classes
1 review

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Data Science Classes

2

Data science techniques

Python, Machine learning, Artificial Intelligence

Answers by Nitesh Kumar Sharma

Answered on 19/10/2023

Ask a Question

Post a Lesson

What is the role of data visualization in data science?

Data visualization in data science serves as a visual storyteller, simplifying complex data into easy-to-understand charts and graphs. It helps analysts and decision-makers spot patterns, draw insights, and communicate findings effectively.
Answers 2 Comments
Dislike Bookmark

Answered on 19/10/2023

Ask a Question

Post a Lesson

How can you handle categorical data in machine learning models?

To handle categorical data in machine learning, you can use techniques like one-hot encoding, where each category becomes a binary feature, or label encoding, which assigns a unique number to each category. These transformations allow machine learning models to work with categorical data effectively. ...more

To handle categorical data in machine learning, you can use techniques like one-hot encoding, where each category becomes a binary feature, or label encoding, which assigns a unique number to each category. These transformations allow machine learning models to work with categorical data effectively.

Answers 1 Comments
Dislike Bookmark

Answered on 19/10/2023

Ask a Question

Post a Lesson

What is the bias-variance decomposition of mean squared error?

The bias-variance decomposition of mean squared error explains how prediction errors can be broken into three parts: bias (systematic errors), variance (fluctuations), and irreducible error (noise). It helps understand how model complexity affects overall prediction accuracy.
Answers 2 Comments
Dislike Bookmark

Answered on 19/10/2023

Ask a Question

Post a Lesson

What is the difference between supervised and semi-supervised learning?

Supervised learning uses labeled data (input-output pairs) to train a model, while semi-supervised learning uses a combination of labeled and unlabeled data, often improving performance by leveraging both types of information. It's like having some answers and trying to find more by using clues from... ...more

Supervised learning uses labeled data (input-output pairs) to train a model, while semi-supervised learning uses a combination of labeled and unlabeled data, often improving performance by leveraging both types of information. It's like having some answers and trying to find more by using clues from the questions you don't know.

Answers 1 Comments
Dislike Bookmark

Answered on 19/10/2023

Ask a Question

Post a Lesson

What are some popular deep learning frameworks?

Some popular deep learning frameworks are TensorFlow and PyTorch, which provide tools to build, train, and deploy deep neural networks for various tasks like image recognition and natural language processing.
Answers 3 Comments
Dislike Bookmark
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