Portfolio of my data analytics assignments completed by me for Academic purposes.
- Applied Confidence interval, hypothesis testing
- Manipulate and summarize data, appraise statistical output, interpret
- Perform descriptive statistics (summary measures, plots & suitable charts, or graphics, perform confidence interval, hypothesis test
- Use contemporary data analysis &visualization tools and recognize
- Apply quantitative reasoning skills to solve complex problems
- Include commentary on the user’s expenditure, usages, patterns, satisfaction levels and demographic, social media engagement
- Conducted predictive analysis of beer data and gave recommendations to improve sales from the historic data.
- Performed basic statistic operations, outlier analysis tests, linear regression, and logistic regression in Excel.
- Developed proposals on where to put effort and money to improve perceptions of product quality and brand image so as to increase the probability of being recommended.
- Created interactive dashboard using Sony Dataset for a upcoming online marketing campaign.
- Insightful data-driven decision making with website
- Using Dynamic filters for performing actions in the graph
- Make interactive for visually appealing effects
- Analyzed Profits & Sales for different types of movies
- Develop a data mining method of classifying imported wine based on price.
- Create a wine origin and marketability
- Best source of wine and optimum price rating ratio.
- Clean-up and explore wine tasting data. Create models like k-nn, naïve Bayes, decision trees.
- Develop a method of estimating rating (points) of wines based on their text attributes.
- Create different models for structured text, unstructured text and mix of structured and unstructured text.
- Create a deployment process.
- To predict whether a cancer is benign or malignant.
- Developed an algorithm that uses SVM to accurately predict (~97 percent accuracy) if a breast cancer tumor is benign or malignant, basically teaching a machine to predict breast cancer.
- Predict a person’s actions based on a trace of their movement using sensors.
- Applied supervised learning algorithms such as K-Nearest Neighbor Classification, Multiclass Logistic Regression with Elastic Net, Support Vector Machine (RBF Kernel), and Random Forest.
- Optimized the best candidate model by hyper-parameter tuning using Grid Search and Cross-Validation; trained a random forest to predict with 99% accuracy.
- Develop a privacy & security issues reporting relation to Cambridge analytical and Facebook situation.
- Provide risks, recognize and apply the relevance Ethical, Regulatory And Governance Issues In Victoria.
- Implementation of K-Anonymity as a Model for Protecting Privacy For an organization.
- Implementation of cloud technology.
- Provide technological solutions.
Energy-Efficiency-for-Building-in-R: Analysis of Energy Efficiency Dataset for Building in R
- Make IT portfolio and business case of gap inc.
- Identify it assets and business value,returns,risks
- Apply RBV and competive advantage over the firm
MIT
If you find any mistakes or you can't figure out something, raise a question. I will get back to you as soon as possible. If you liked what you saw, want to have a chat with me about the portfolio, work opportunities, or collaboration, shoot an email at gupta.sha@outlook.com