Skills

Statistics: 

• Descriptive Statistics: Mean, Mode, Median

• Variability: Standard Deviation, Variance, Range, Percentile, Quartile

• Correlation: Positive, Negative

• Probability Distribution

• Regression:Linear Regression, Logistic Regression

• Pie Chart, Bar Chart, Histogram 

Machine Learning: 

• Supervised Learning : Linear Regression, Logistic Regression, Decision Trees, K-Nearest Neighbors, Naive Bayes, Support Vector Machines, Random Forest

• Unsupervised Learning : K-means Clustering, Hierarchal Clustering, Apriori Algorithm, Neural Networks etc. 

Data Analysis Library (Python)  : 

• NumPy, Pandas

• Matplotlib, SciKit-Learn, Seaborn

Working Areas  : 

• Digital Image Processing

• Image Denoising and Compression

• Encoding and Decoding

• Computer Vision

Application Development (Android - Java & Kotlin) :

• Different types of components

• UI design with XML

• Different types of design layouts: Constrain Layout, Linear Layout, Relative Layout, Frame Layout etc.

• Database : Postgre SQL, Shared Preference

• Coding architecture pattern : MVVM (Model - View - View Model), MVP (Model - View - Presenter)

• Dependency Injection, APIs, JSON

• Google Map SDK & Google Map APIs

• Git, GitHub

• Different types of third-party libraries

• Working Platform : Visual Studio

• Working Areas : Data Collection and Analysis, Computer Vision, Digital Image Processing.

Web Design :

• HTML

• CSS and Tailwind

• Java Script (Basic)

• NodeJS

• ReactJS

• Redux

• Router

• ExpressJS

• Material UI

• MongoDB