Inplant Training Project

PROFESSIONAL SUMMARY:

EDUCATION QUALIFICATION:

TECHNICAL SKILLS:

ACHIEVEMENTS:

RENURAJ YENNAWAR

E-Mail:********.*********@*****.***

Looking for Data Scientist/Artificial intelligence/Deep learning/Computer vision/Machine learning jobs only.

• Achievement-driven professional with an experience of 1 year in Python programming.

• Experience of Machine learning algorithms like Linear and Logistic Regression, KNN, Support Vector Machines (SVM), Decision trees, Random Forest, Gradient Boosting, XGBoost and K-Means Clustering.

• Skilled in libraries like Numpy, Pandas, Matplotlib, Seaborn, Scikit Learn, Keras and OpenCV.

• Strong Mathematical foundation and good in Statistics.

• Feature engineering in Python – Missing value treatment, outlier handling, data transformation, feature selection and reshaping data using Python packages like Numpy, Pandas and Scikit Learn.

• Good knowledge of Deep Learning (DL) and ample hands-on with Neural Networks, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks

(RNN) and Long Short Term Memories(LSTM).

• Basic Understanding of Computer Vision techniques like Image pre-processing, Image Segmentation, Object detection, Object recognition etc.

• Basic Understanding of Natural Language Processing (NLP) techniques like tokenization, stemming, lemmatization, word2vec etc.

• Good at fundamentals of SQL.

• Good at fundamentals of C,C++,JAVA

• Understanding of Image Processing, DSP Architecture subjects.

• Self-motivated team player with good communication and presentation skills.

• Good analytical and problem solving skills.

• Completed Masters of Engineering (M.Tech) in Signal Processing (Electronics and Telecommunication) from College of Engineering,Pune (COEP) in 2020.

• Bachelor of Engineering (B.E) in Electronics and Telecommunication (E&TC) from MPGI College of Engineering, Nanded under SRTM University in 2017.

• HSC from N.E.S.Science College, Nanded, Maharashtra State Board in 2013.

• SSC from Nagarjuna Public School, Nanded, Maharashtra State Board in 2011.

• Programming Languages: Python, Machine Learning, Artificial Intelligence, Deep Neural Networks, Convolutional Neural Network, Numpy, Pandas, Sklearn, Tensorflow, Keras, OpenCV, C, Java(basics), C++(basics).

• Databases: MySQL

• Visualization Tools and Libraries: Basic understanding of Matplotlib and Seaborn, Code compressor studio(CCS),MATLAB, Flask for Model Deployment.

• Platforms and Misc.: Anaconda, Jupyter Notebook, Google Colab, Xilinx.

• Participated in Research Conclave 2020 organized by COEP Pune in association with SGSITS-INDORE and MTU- Imphal under TEQIP-III in July 2020.

• Workshop of Data Science organized by GreyAtom for Banking Project Prediction using Machine Learning Algorithms in June 2020.

• Workshop of Drones making and its Fundamentals organized by FlytBase at COEP in 2019.

• Participated in International Conference Paper Presentation organized by MPGI, College of Engineering, Nanded by SRTMU for year 2016-17.

• Participated in KRATOS Technical Events organized by MPGI, College of Engineering, Nanded in 2016.

• Done Inplant Training at FM Station(Akashwani Kendra), Nanded in 2015-16.

• Participated in National Science Exhibition organized by SRTM University, Nanded in 2006-07. INTERNSHIP EXPERIENCE Aug 2020 – March 2021

DATA SCIENCE PROJECTS:

Project 1: Measurement of Zone of Inhibition of Antibiotics using CNN Project 2: Twitter Sentiment Analysis

• March 2021 – Advance Data Science course with Hands-on GPU from Netzwerk Data Science Academy an ISO certified institute.

• Dec 2020 – SQL For Begineers by Udemy

• Nov2020 – Python for Data Science & Machine Learning by Udemy

• July 2020 – Data Visualization Using Python by Great Learning Company Netzwerk Academy

Role Data Science Intern

Technologies used Python, Machine Learning, Deep Learning, Computer Vision, NLP Responsibilities • Understanding the problem statement, analysing the problem, building architecture on how to solve the problem.

• Collecting, cleaning, transforming and analysing the data.

• Building Machine Learning and Deep Learning models.

• Training and testing ML/ DL models using Tensorflow.

• Learning Flask for Model Deployment.

Description • There were 150 biomedical images of anti-bacterial samples taken from hospitals and motto was to find diameter of zone of inhibition of antibiotics. Using CNN and Image Processing Techniques and YOLO Arch for object detection it was done. Moreover, it is detected that which bacteria is susceptible towards an antibiotic.

• All the basic Image Processing Techniques like Canny Edge Detection, Gaussian Filtering were used.

Tools and Technologies

used

Python, Numpy, CNN,YOLO, Pandas, Jupyter Notebook(Anaconda 3) Description • The project aims to analyze various tweets by people and to classify whether the tweet is positive, negative or neutral.

• Sentiment Analysis is done on all tweets using NLP keywords such as Tokenizer, Vectorizer.

Tools and

Technologies used

Python, Numpy, Pandas, Matplotlib, Seaborn, NLP, Tensorflow,Keras Project NLP(Natural language processing)

CERTIFICATIONS:

Project 4: Banking Prediction Analysis

Project 5: Face Mask Detection

Personal Details:

Description • The project basically deals with classification problem.

• In this, there are 60,000 images of various classes such as Aeroplane, truck, car, etc. out of this, 50,000 were used for training and 10,000 for testing.

• CNN is used here for getting best results with more accuracy.

• Using CNN, the accuracy increases and the classification is done successfully.

Tools and Technologies

used

Python, Numpy, Pandas, Matplotlib, Seaborn, CNN, Tensorflow,Keras Description • The aim of the project is to analyze the Banking activities.

• The aim is to predict the loan for customer depending upon his fixed deposit and savings. The model will decide to give customer loan or not.

• Applied classification techniques and the following were the steps to followed :

• Part 1:

1 . Business Understanding

2 . Data Understanding

• Part 2:

3. Data Preparation

• Part 3:

4 . Data Modeling

5 . Results Evaluation

Tools and Technologies

used

Python, Numpy, Pandas, Matplotlib, Seaborn, Machine Learning Algorithms like Decision Tree, Random Forest, SVM.

Description • This model is built using Convolution Neural Networks.

• Used Frontal Face Haar-cascade classifier to detect the faces by using the webcam. These face images are then passed to our model to detect whether or not a face contains the mask.

Tools and Technologies

used

Python, Numpy, Matplotlib, OpenCV, CNN

DOB 02/05/1995

Address “Bhagwati”,Kailash Nagar(East),Shyam Nagar Road, Nanded(Maharashtra)

Languages Known English, Hindi, Marathi,French

Project 3: CiFar 10 Image Classification using CNN

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