R RAVI TEJA #*/**,kaminihall(village),

EMAIL: adnrmv@r.postjobfree.com Halarvi(mandal),kurnool-518348

Contact No: +91-817*******

CAREER OBJECTIVE:

I am Ravi who aims to be able to find an exciting and challenging entry-level position in the

Data science industry alongside a company who will continuously motivate and drive me to do my best

and improve on my skills and abilities in order to be able to assist the company in achieving its company mission and goals.

ACADEMIC QUALIFICATION:

B.E in Computer Science and Engineering from Rajarajeswari College of Engineering, Visvesvaraya Technological University @ Mysore Road, Bangalore.

Percentage: 60%

12th from SRI CHAITYANA junior College, Kurnool. Percentage: 84.70%.

10th from INDUS School, Kurnool. CGPA: 8.2

TECHNICAL SKILLS:

Programming Languages:

C, Java, Python, R, Machine Learning, Data Analysis

MarkUp Languages:

HTML, CSS

Database Language:

SQL (DBMS)

Project 1 : Sky Analytics

AI could help to process data quicker, meaning cases of lung cancer could be spotted sooner and more lives could be saved.

Machine learning is not new to cancer research. Today machine learning methods are being used in a wide range of applications ranging from detecting and classifying tumors via X-ray and CRT images to the classification of malignancies from proteomic and genomic (microarray). In other words machine learning has been used primarily as an aid to cancer diagnosis and detection.

It has only been relatively recently that cancer researchers have attempted to apply machine learning towards cancer prediction and prognosis.

In cancer prediction/prognosis one is concerned with three predictive points

the prediction of cancer susceptibility (i.e. risk assessment) - Predicting the likelihood of developing a cancer prior to the occurrence of the disease.

the predicting the probability progression of cancer Predicting the probability of cancer based on medical tests and medical journals.

the prediction of cancer recurrence - predict the likelihood of redeveloping cancer after to the apparent resolution of the disease.

the prediction of cancer survivability - predict an outcome (life expectancy, survivability, progression, tumor-drug sensitivity) after the diagnosis of the disease.

Project 2 : Sky Analytics

OBJECTIVE: Successful Marketing is sending right content over right channel at right time to right Customer.

TECHNIQUES: RFM, LTVC, Segmentation and Clustering

MODEL BUILDING PROCESS:

Collected customers data from various medium like websites, landing pages, social media and also used marketing tools that captures user behavior. Based on which, we remove duplicate date and update the missing values. This information helps us to identify the most important customer more accurately based on their Frequency, Monetary and Recency, rank the customers. Based on which, RFM score is generated.

RFM score helps us to identify the best customers and to retain our best customer we will provide them some benefits and calculate LTVC. As long as the LTVC > Customer cost of acquisition, marketing expense in acquiring the customer was well spent.

Repeat the same exercise on different segments of customer

Base data exploration of the large dataset provided by the client which helped us set parameters to work upon.

Finding the Missing or Null value data points (if any) in the the datset and took appropriate actions on it.

Seggregated the Categorical data from the Numerical and had the data ready for the further analysis.

Played a major role in data preprocessing, and data Normalisation.

With the help of Scikit learn library successfully splitted the data into Train and Test sub datasets.

Collaboratively worked with team, in Model selection to achieve best possible re

sult.

With the help KNN algorithm we predicted the cancer possibilities and are still working on to get the prediction more accurate.

ACADEMIC PROJECTS:

Project name : Space Shooter Gaming project

Language used : c++ .

Description : The project is about game and build using only coding by using the turbo engine and got a second price for this project.

Project name : air quality monitoring using sensing devices in urban cities

Language used : Python and ml

Description : The project is designed based on the machine learning we use the regression model And predict the present air quality.

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ACHIEVEMENTS:

Organized an event at National Level Symposium named TRIGGER September 2018.

Organized an IEEE at International Level in May 2018.

Published a paper in a IACAT conference.

Got an certification on the decision tree training in Analytics Vidhya online platform.

I have training on the data science domain.

INTERNSHIPS:

I have completed my internship on the full stack development. And got certified with the project NIRMANN.

STRENGTHS:

Communication skills.

Decision making ability.

Positive Attitude.

PERSONAL DETAILS:

Fathers Name: Mr. R Vajragiri

Mothers Name: Mrs. R Aruna

Date of Birth: 02/07/1999

Languages known: English, Hindi, Kannada, Telugu,.

Hobbies and Interests: Playing, Listening to Music

DECLARATION:

I hereby declare that the above information is correct to the best of my knowledge and belief.

Place: Bangalore

Date: 15-07-2021 (R RAVI TEJA)

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