Ashish G.

Ashish G.

Software Industry profile based in Chennai having 3 Years of Experience with Data Science

Chennai , India

Experience: 4 Years

Ashish

Chennai , India

Software Industry profile based in Chennai having 3 Years of Experience with Data Science

4 Years

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About Me

Top skills:

Python, Machine learning, Microsoft power BI, Tableau, SQL, Predictive modelling, pyspark

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Portfolio Projects

Gas Turbine combined cycle

Company

Gas Turbine combined cycle

Role

Data Scientist

Description

Gas Turbine Combined Cycle
Performed preprocessing on the structured data.
Performed Exploratory Data Analysis(EDA) on data to identify data distribution
and trend by visualizing data using analytical tools like python, matplotlib and
plotly.
Performed Descriptive statistics to understand Central Tendency, Measure of
variability, skewness, variance and standard deviation.
Implemented Z score techniques to find outliers in the data and replaced the
data with the median value.
Performed hypothesis testing on the data like Normality tests, Correlation tests,
parametric statistical hypothesis and non parametric statistical hypothesis tests.
Implemented Recursive Feature elimination with Random forest technique for
feature selection.
Implemented KNN algorithm for pattern recognition in the feature space to
identify reduced efficiency in the power plant operations.
Implemented regression models like Linear Regression, SVR, Random Forest
Regression to predict the efficiency of the turbine.
Performed optimization on the predicted efficiency.
Performed sensitivity analysis to check the effect of the features on the
predicted outcome of a machine learning model.
Developed API with Flask to deploy Machine learning model and different
visualization to the dashboard.

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Tool Analysis

Company

Tool Analysis

Role

Data Scientist

Description

Working with an structured log as well as unstructured log for different tools.
Converted the unstructured log to structured format.
Performed preprocessing on the log by removing the unwanted fields and
dropping the row containing null values.
Analysed the log file to understand the usage of the tools by various teams.
Analysed how the usage of the tool increases productivity for each team.
Analyse the types of jobs run by each team and understand the pattern of the
result produced by the tool.
Formulate action plans as how to fix the error when the tool find the errors
which are previously know.
Increase the performance of the tool by reducing the manual fix points of the
errors and autocorrection of the errors faced.
Performed kmeans clustering to group similar kind of error together and
construct a highly optimized report for users

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