Nagesh Perumandla M: +91-955******* E: ada5rl@r.postjobfree.com

Python Machine Learning (Supervised & Unsupervised learning and Clustering) Deep Learning(DNN,CNN & RNN) SQL

PROJECTS

QUORA QUESTION PAIRS SIMILARITY, Jul-Aug 2019

This is my first major project that i have started, In this project i have used basic & advanced feature extraction techniques on text features and after data cleaning and data pre-processing I have applied base ML models Logistic regression, linear SVM, XG-BOOST and compared all models based on log loss performance metric.

TOOLS: Python3 Jupyter notebook Sklearn Matplotlib Pandas Numpy Seaborn. GITHUB : https://github.com/Nageshpermand/Quora_questionpairs_similarity PERSONALIZED CANCER DIAGNOSIS, Jul-Aug 2019

In this project, classified the given genetic variations/mutations based on evidence from text based clinical literature.

TOOLS: Python3 Jupyter notebook Sklearn Matplotlib Pandas Numpy Seaborn. GITHUB : https://github.com/Nageshpermand/Personalized_cancer_diagnosis HUMAN ACTIVITY RECOGNITION: Jul-Aug 2019

This project is to build a model that predicts the human activities by using Base ML models such as Logistic regression, Linear SVC, Kernal SVM, Decision Tree, GBDT and Deep Learning model LSTM with different units and different layers after that compared all models based on accuracy.

TOOLS: Python3 Jupyter notebook Sklearn Matplotlib Pandas Numpy Seaborn TF Keras GITHUB : https://github.com/Nageshpermand/Human_Activity_Recognition WORK SAMPLES

GITHUB PROFILE: https://github.com/Nageshpermand

MEDIUM BLOG LINK: https://medium.com/@nagpermand

2

CERTIFICATION TRAINING COURSE ( AAIC TECH. PVT.LTD,) Machine Learning & Deep Learning Course from

(Appliedai Course) JUL-AUG 2019

Python and ML Libraries :

I have learned python programming from scratch at the initial stage of this course. Linear Algebra and statistical concepts :

I’ve learned various statistical concepts and LA concepts and i was able to interpret those concepts.

Data Analysis :

I’ve learned how to perform the data preprocessing, Exploratory Data Analysis and visualization techniques before building base ML models. ML algorithms and Deep Learning models:

In this phase of the course, I’ve learned a sufficient amount of theory with a lot of applied aspects of the concepts for all ML base models and some other deep learning models, While learning all concepts i have submitted various assignments. Workshop on “The Apparel recommendation engine”

Here I have learned on how to build content-based recommendation system by using various ways to vectorize text features and also i learned add weights on different features, I’ve recommended most similar products.

EDUCATION

B.E in Electronics and Communication Engineering (2014 – 18) Methodist College Of Engineering and Technology, Hyderabad. Diploma in Electronics and Communication Engineering (2012 – 15) Rathnapuri Inistitute of Technology College of Polytechnic, Hyderabad. SSC Rdf Matendla School 2011

PERSONAL INFO

DOB: AUGUST 1995

LANGUAGES: English (Fluent). 2. Telugu(Mother Tongue). 3. Hindi(Intermediate).

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