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About
Being a maths graduate, I am always inclined towards data and I love to play with the data . I always wanted to analyse them and draw conclusions from them. Pursued Data Science certification from Springboard – Specialising in Certified in Python, SQL, Data Science, Deep learning, and Machine Learning. Adept in creating data regression models, using predictive data modelling, and analyzing data mining algorithms to deliver insights and implement action-oriented solutions to complex business problems Skills stack: 1. Programming/Scripting: Python, SQL 2. Data Engineering: Data pre-processing, Data cleaning, exploratory data analysis, Data visualization, Feature engineering. 3. ML: Linear/Logistic regression, Decision Trees, Support vector machines, Random forest, XG Boost, K-Nearest Neighbours. 4. Big data frameworks: PySpark. 5. Libraries/Math: Descriptive/Inferential statistics, probability, Numpy, Pandas, Scikit-learn, NLTK, Gensim, Seaborn, Plotly, Matplotlib, imblearn.see more
Experience
Tell us about your professional experience
Tell us about your professional experience
Education
Where did you complete your basic education from?
Where did you complete your basic education from?
Accomplishments
Certifications
Certified Data Scientist  
Issued : Jan 2021
Advanced SQL for Data Scientists  
Issued : Nov 2020
Introduction to Spark SQL and DataFrames  
Issued : Nov 2020
Data Analysis Concepts  
Issued : Sep 2020
Estimates & Measures  
Issued : Sep 2020
Machine Learning Introduction  
Issued : Sep 2020
Data Science Overview  
Issued : Aug 2020
About
Being a maths graduate, I am always inclined towards data and I love to play with the data . I always wanted to analyse them and draw conclusions from them. Pursued Data Science certification from Springboard – Specialising in Certified in Python, SQL, Data Science, Deep learning, and Machine Learning. Adept in creating data regression models, using predictive data modelling, and analyzing data mining algorithms to deliver insights and implement action-oriented solutions to complex business problems Skills stack: 1. Programming/Scripting: Python, SQL 2. Data Engineering: Data pre-processing, Data cleaning, exploratory data analysis, Data visualization, Feature engineering. 3. ML: Linear/Logistic regression, Decision Trees, Support vector machines, Random forest, XG Boost, K-Nearest Neighbours. 4. Big data frameworks: PySpark. 5. Libraries/Math: Descriptive/Inferential statistics, probability, Numpy, Pandas, Scikit-learn, NLTK, Gensim, Seaborn, Plotly, Matplotlib, imblearn.see more

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