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Pooja Krishnakumar Data science
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Proficient in data cleaning, transformation, and exploration.
Expertise in visualizing data using tools like Matplotlib, Seaborn, and Plotly.
Skilled in creating dashboards and reports using Tableau and Power BI.
Statistical Analysis:
Strong understanding of statistical concepts and hypothesis testing.
Experience with statistical software like R and SAS.
Machine Learning:
Knowledgeable in supervised and unsupervised learning algorithms such as regression, classification, clustering, and dimensionality reduction.
Hands-on experience with machine learning frameworks and libraries like Scikit-learn, TensorFlow, and Keras.Programming:
Proficient in Python and R for data analysis and machine learning.
Experience with SQL for database querying and management.
Big Data Technologies:
Familiarity with big data tools and frameworks such as Hadoop, Spark, and Hive.
Experience with cloud platforms like AWS, Google Cloud, and Azure for big data processing and storage.
Data Management:
Experience in data entry, management, and database administration.
Skilled in ensuring data integrity, consistency, and security.
Projects:
Developed predictive models to forecast sales using machine learning algorithms, resulting in a 15% increase in forecast accuracy.
Implemented a customer segmentation analysis to identify key customer groups, leading to targeted marketing strategies that increased customer engagement by 20%.
Created interactive dashboards for business stakeholders to monitor key performance indicators and make data-driven decisions.
Education:
Courses in Calculus, Ordinary and Partial Differential Equations, Linear Algebra, and Abstract Algebra, with experience in teaching these subjects at the college level.
Expertise in visualizing data using tools like Matplotlib, Seaborn, and Plotly.
Skilled in creating dashboards and reports using Tableau and Power BI.
Statistical Analysis:
Strong understanding of statistical concepts and hypothesis testing.
Experience with statistical software like R and SAS.
Machine Learning:
Knowledgeable in supervised and unsupervised learning algorithms such as regression, classification, clustering, and dimensionality reduction.
Hands-on experience with machine learning frameworks and libraries like Scikit-learn, TensorFlow, and Keras.Programming:
Proficient in Python and R for data analysis and machine learning.
Experience with SQL for database querying and management.
Big Data Technologies:
Familiarity with big data tools and frameworks such as Hadoop, Spark, and Hive.
Experience with cloud platforms like AWS, Google Cloud, and Azure for big data processing and storage.
Data Management:
Experience in data entry, management, and database administration.
Skilled in ensuring data integrity, consistency, and security.
Projects:
Developed predictive models to forecast sales using machine learning algorithms, resulting in a 15% increase in forecast accuracy.
Implemented a customer segmentation analysis to identify key customer groups, leading to targeted marketing strategies that increased customer engagement by 20%.
Created interactive dashboards for business stakeholders to monitor key performance indicators and make data-driven decisions.
Education:
Courses in Calculus, Ordinary and Partial Differential Equations, Linear Algebra, and Abstract Algebra, with experience in teaching these subjects at the college level.
Subjects
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Maths Beginner-Expert
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Data Science (Mathematics) Beginner-Expert
Experience
No experience mentioned.
Education
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bsc mathamatics (Jul, 2018–May, 2020) from Kerala University, Trivandrum
Fee details
₹1,000–5,000/week (US$11.89–59.46/week)
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Jawaharlal Nehru Stadium, Pragati Vihar, New Delhi, Delhi, India
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Can travel:
15.54 mi (25.0 km)
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- Last login: Jul 14
- Registered: Jul 14
- Total Teaching exp: 2.0 yrs.
- Teaches online: Yes
- Online Teaching exp: 2.0 yrs.
- Teaches at student's home: Yes
- Homework Help: Yes
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Gender: Female
- Works as: Individual teacher
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Fee:₹1,000–5,000/week(USD 11.89–59.46/week)
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