Sri Gouri Patnam

Data Scientist familiar with gathering, cleaning, organizing and visualizing data for use by technical and non-technical personnel. Advanced understanding of statistical, algebraic and other analytical techniques. Highly organized, motivated and diligent with significant background in Data Science.

• Classification of Breast Cancer Diagnosis:

Objective: To classify the diagnosis of breast tumors identified using biopsy into benign or malignant using Wisconsin Breast cancer data from UCI.

Key skills: Python, EDA, Principal component analysis, SVM, Decision trees, K-Nearest Neighbor, Ensemble methods.

• Image Classification Using Convolutional Neural Network:

Objective: To demonstrate the image classification using CNN using the Fashion-MNIST dataset available in Keras.

Key skills: Python, Exploratory data analysis, Deep Learning, Neural Network (CNN)

• Life expectancy prediction:

Objective: To predict how long a new-born person can expect to live if current death rates do not change and to examine the impact of socio-economic factors on life expectancy based on various factors using World Development Indicators dataset (2019)

Key skills: EDA, Data Cleaning, Linear Regression, R, Descriptive statistics (ANOVA)

• Analysis and sale price prediction on Housing data:

Objective: To analyze overall Condition of house and based on the house type, size, neighborhood amenities,and other factors that may influence demand and supply

Key skills: R, EDA, Machine learning algorithms like Linear Regression, K-means clustering

• Causal Inference on Infant Health Development Program Data:

Objective: To predict the Individual Treatment Effect (ITE), the Average Treatment Effect (ATE) and the Precision in estimation of Heterogeneous Effect (PEHE), using IHDP (Infant Health Developed Program data (Hill, 2011))

Key skills: Python, Matplotlib, Exploratory data analysis, PCA, Random Forest regressor, Linear Regression, X-Learner.

Explore Core Data Concepts in Microsoft Azure by Coursera.