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Ashis Sahu Data Science trainer in Bangalore

Ashis Sahu

locationImg Whitefield, Bangalore
10 yrs of Exp
rsIcon 300 per hour
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Transforming Data into Actionable Insights: Experienced Data Scientist with FMCG knowledge

Online Classes
I am a seasoned Data Scientist with over a decade of experience, specializing in the FMCG (Fast-Moving Consumer Goods) industry. My journey in the data domain has equipped me with a versatile toolkit, including Python, PySpark, Pandas, NumPy, and more. I excel in Machine Learning, both supervised and unsupervised, leveraging data for predictive analytics. My passion for NLP and AI, particularly large language models and generative AI, enables me to extract actionable insights from unstructured data.

Languages Spoken

English Proficient

Hindi Proficient

Education

BPUT 2012

Bachelor of Technology (B.Tech.)

Address

Whitefield, Bangalore, India - 560066

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Teaches

Data Science Classes

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Data Science Classes

10

Data science techniques

Artificial Intelligence, Python, Machine learning

Reviews

No Reviews yet!

Answers by Ashis Sahu

Answered on 31/05/2024

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Imagine you have a group of friends, and you want to categorize them based on their movie preferences. Each friend can prefer different genres, like Action, Comedy, Drama, etc. Let's say you have the following data: | Friend | Favorite Genre 1 | Favorite Genre 2 ||---------|-------------------|------------------||... ...more

Imagine you have a group of friends, and you want to categorize them based on their movie preferences. Each friend can prefer different genres, like Action, Comedy, Drama, etc. Let's say you have the following data:

| Friend | Favorite Genre 1 | Favorite Genre 2 |
|---------|-------------------|------------------|
| Alice | Action | Comedy |
| Bob | Drama | Comedy |
| Carol | Action | Drama |
| Dave | Comedy | Action |
| Eve | Drama | Action |

Fuzzy K-Modes helps in grouping friends based on their movie preferences, allowing for overlaps where a friend can belong to multiple groups to varying degrees. This approach is particularly useful when preferences are not clear-cut, and people can like more than one genre.

Answers 6 Comments
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Teaches

Data Science Classes

Class Location

Online class via Zoom

Student's Home

Tutor's Home

Years of Experience in Data Science Classes

10

Data science techniques

Artificial Intelligence, Python, Machine learning

No Reviews yet!

Answers by Ashis Sahu

Answered on 31/05/2024

Ask a Question

Post a Lesson

Imagine you have a group of friends, and you want to categorize them based on their movie preferences. Each friend can prefer different genres, like Action, Comedy, Drama, etc. Let's say you have the following data: | Friend | Favorite Genre 1 | Favorite Genre 2 ||---------|-------------------|------------------||... ...more

Imagine you have a group of friends, and you want to categorize them based on their movie preferences. Each friend can prefer different genres, like Action, Comedy, Drama, etc. Let's say you have the following data:

| Friend | Favorite Genre 1 | Favorite Genre 2 |
|---------|-------------------|------------------|
| Alice | Action | Comedy |
| Bob | Drama | Comedy |
| Carol | Action | Drama |
| Dave | Comedy | Action |
| Eve | Drama | Action |

Fuzzy K-Modes helps in grouping friends based on their movie preferences, allowing for overlaps where a friend can belong to multiple groups to varying degrees. This approach is particularly useful when preferences are not clear-cut, and people can like more than one genre.

Answers 6 Comments
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