kadimi619 Goto Github PK
Name: K Chandra Teja
Type: User
Bio: Data Science Enthusiast | Post Graduate Student in Data Science and Engineering at Great Learning | Actively looking forward to work in the field of Analytics.
Location: Hyderabad
K Chandra Teja's Projects
exploratory-data-analysis
Uni-variate/Bi-variate Analysis , Boxplot , Violin plot ,IQR , Basic EDA pre-processing steps, Heatmap ,Multi-variate analysis
insurance-claim-prediction---regression-model
A key challenge for the insurance industry is to charge each customer an appropriate premium for the risk they represent. Predicting the cost of claims in an insurance company is a real-life problem that needs to be solved in a more accurate and automated way.
logistics-supply-chain-classification
Logistics in supply chain plays a crucial role in the inventory management of the raw materials required for the operations, The firm will like to make use of data driven approach using ML models so that they can predict which order can get delayed in the future and hence take preventive measures.
numpy-pandas-visualization-mini-project
Understanding about the dataset Employee Health using Data -preprocessing steps using Numpy/Pandas/Seaborn/Matplotlib
power-bi-project
: To design and deliver End-to -End Business intelligence solution (Dashboard) to track KPIs (Sales, Revenue,Profit,Returns) ,compare regional performance, analyze product-level trends and forecasts and identify high-value customers.
python-e-commerce-shipment-project
Use of Lists /Dictionaries/List and Dictionary Comprehensions / for loops to solve these mini project about E-commerce shipment
sql-mini-project-on-ipl-dataset
Use of JOINS(INNER/LEFT/RIGHT/FULL OUTER JOIN)/GROUP BY / HAVING/AGGREGATE FUNCTIONS AND SQL FUNCTIONS /SQL KEYWORDS
tableau-airport-project
We create a Dashboard to display the San Francisco Airport Details. We make use concept of Calculated Fields, Filters and other important visual charts to explain our Dashboard
vehicle-loan-default-prediction
Financial institutions sustain huge number of losses due to the default of vehicle loans. This has led to the tightening up of vehicle loan policies and increased vehicle loan rejection rates. So, this requires a study to estimate the parameters of vehicle loan default.
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