Yuvraj Pandey

Data Scientist familiar with gathering, cleaning and organizing 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 AI and Big Data Technologies .

Certified Data Scientist License -IAB1120172228

1.Project;-Inventory Forecasting

Project Description: The case business case is on the inventory management. Keeping
Inventory of spare in various service centre to the market demand is
always a challenge as most service centres spends significant amount
in spare parts inventory costs. In spite of this, availability of spare
parts is been one of the problem areas.

ML – Algorithm are used Prophet,LSTM,ARIMA,Ar

2.Project;- Home Loan Default - Risk Management-predict

Project Description: How capable each loan applicant is competent in repaying the loan. An existential problem for any Loan providers today is to find out the Loan applicants who are very likely to repay the loan. This way companies can avoid losses and incur huge profits.

ML – Algorithm are used 1. Logestic Regression 2.DecisionTreeClassifier 3.RandomForestClassifier 4.XGBoost Classifier

3.Project;- HandwrittenDigits

Project Description: Classification of given image of a handwritten digit into one of 10 classes representing integer values from 0 to 9, inclusively.

The MNIST dataset is an acronym that stands for the Modified National Institute of Standards and Technology dataset. It is a dataset of 60,000 small square 28×28 pixel grayscale images of handwritten single digits between 0 and 9. Our target here to create a ML model to classify the image of a handwritten digit into one of 10 classes representing integer values from 0 to 9, inclusively.

ML – Algorithm are used SVM,Random forest Classifier,KNN classifier,CNN with Tensorflow

4.Project;-Insurance Claim Prediction

Project Description: Predict if a driver will file an insurance claim next year. Inaccuracies in car insurance company’s claim predictions raise the cost of insurance for good drivers and reduce the price for bad ones.

ML – Algorithm are used 1.Logestic Regression with Smote 2.DecisionTreeClassifier with PCA 3.RandomForestClassifier 4.XGBoost Classifier with PCA

5.Project;- Game Winner Prediction

Project Description: Predict finishing placement based on final stats. This is a PUBG game data set. The data set contains a large amount of anonymized game stats of a single player with all match type. Our target here to create a ML model to predict the finishing placement of a player based on the final stats.

ML – Algorithm are used 1.Linear Regression 2.Random forest Regressor (with sampled data set only) 3.XGBoost regressor 4.ANN 5.CNN with Tensorflow

6.Project;-EDA on IPL Dataset

Project Description: Predict won after first batting and which team won highest number of matches by doing first batting. Predict

how many times a team won match after wining the toss

Univariate and Bivariate analysis done by using Python

7. Project;-Stock Price Prediction

Project Description: Apple Stock demonstrate prediction for next 10 days

By using Tiingo plateform fatch the data through API (api_key) from 2017-02-01 to 2022-01-25 and do EDA and features engineering by using python some analysis done.

Python libraries are used such as Matplotlib,Sklearn,Numpy and Tensorflow keras

8. Project;-Covid 19. Prediction