Venkata Sreenivasulu Manchikanti

Complex problem-solver with analytical and driven mindset. Dedicated to achieving demanding development objectives according to tight schedules while producing impeccable code. Detail-oriented team player with strong organizational skills. Ability to handle multiple projects simultaneously with a high degree of accuracy.

CEHV10(CERTIFIED ETHICAL HACKER)

  Habana Automation Framework Tool ( To develop a automation Framework by using python, ML and AI):

Responsibilities:

Understanding the Requirements. 

Designing of Flowchart.

Framework Development.

Code Implementation. 

Preparing test scenarios. 

Execution of test scenarios 

In validating of server platform, BIOS Firmware, Silicon and OS. Which includes of Lab setups, board briug up. Hands on experience in Firmware, BIOS and UEFI validation.
Hands on experience in PCle, stress, Ras, boot&reset, Firmware update, Domain's validation.
Validation on Bios chipset by installing IFWI release to check the BIOS processing.
Experience in working with Linux platform.
Experience in writing test cases and execution of test cases.
Hands on experience in Functional testing of Intel's Gaudi Al processor on Linux.
Executing RAS, PID, stress, stability, PCle OOB, Inband, boot&reset, manageability test cases on daily basic on all the cards HL-200 in server board.
Tasks involve flashing OS & installing the firmware manually and automatic process with SVT tool.
Responsible for test case preparation, modification  and execution.

modification and execution
 

Diamond Price Prediction (04/2023-05/2023):

I have taken a dataset with 200,000 rows 

 I have created an environment for a Python project. 

The first step I took was conducting an Exploratory Data Analysis (EDA) process 

The second step I took was performing feature engineering

 After performing feature engineering, the next step I took was seeking expert opinions on the columns related to cut, clarity, and color. Based on those opinions, I 

      proceeded to encode the respective features. 

 I took was segregating the dataset into numerical columns and categorical columns. This separation helps in analyzing and processing different types of variables 

      effectively 

the next step I took was implementing a pipeline. This pipeline encompassed several data preprocessing steps, including checking for missing values, handling feature

     scaling, and performing ordinal encoding. 

I took was splitting the data into training and testing datasets. This division is crucial for evaluating the performance and generalization ability of machine learning models. 

I developed a function that trained various regression models, including Linear Regression, Lasso Regression, Ridge Regression, and Elastic Net. Within this function, I

     calculated several evaluation metrics to assess the performance of these models, including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R2 Score. 

 I deployed it in MongoDB. 

  Youtube Web Scraping (02/2023 - 03/2023):

Proficiency in web scraping tools and technologies such as Python, Beautiful Soup, Pandas Data Frame, Numpy, Urlopen, OS.

Ability to extract images from YouTube videos using various techniques such as parsing HTML.

Experience in cleaning and preprocessing scraped data to ensure accuracy and reliability.

Ability to work with large volumes of data and extract meaningful insights.

Supermarket Sales in Data Science | Data Visualization (12/2022 - 01/2023):

Analyzed the data and which products were more sales in supermarket more females or males or going and analysis the product was future we can buy or not.

Proficiency in Supermarket Sales and technologies such as Python, Pandas Data Frame, Numpy, Matplotlib, Seaborn, Scipy.

Worked with large volume of dataset for Visualization. Cleaning the unwanted data to ensure accuracy and reliability. understanding of retail industry trends for upcoming bussiness