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Python Data

Location:
Bangalore, Karnataka, India
Posted:
December 19, 2019

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Resume:

Amit Jagadish Sure

Versatile, Explorer

ada3zz@r.postjobfree.com

+91-959*******

https://linkedin.com/in/amit-js-51593714a

https://github.com/amitjslearn

https://www.kaggle.com/amitjslearn

https://stackoverflow.com/users/8063334/amit-js

PROJECTS

Kannada MNIST (Kaggle)

- Recognize Kannada digits 0-9 - created a CNN with max-pooling, dropout regularization, batch normalization - achieved 98.8% accuracy - Also got good results with Transfer Learning using VGG16 and RESNET, trying to improve the results by transfer learning.

Sentiment Analysis on Comedians

- Comparing different comedians using NLP - Data gathering, data cleaning, reiterating - Conducted EDA and Sentiment Analysis Semantic Textual Similarity

-Unsupervised - Transfer Learning (fine-tuning) - used Doc2Vec, Transformers, BERT, using cosine similarity - Trying Transfer Learning With BERT (and its derivatives)

Predicting and forecasting stock prices

- Done featuring engineering - Used LSTM and NN (Sequential) for modeling - For Yes Bank and Google stock price - The model was able to capture the ups and downs in the price

Wordipy (Python)

- A dummy package for preprocessing text in NLP applications - Converts spoken English to written English - Packaged using setup.py - With a good documentation

AutoTimer (Python)

- Contributed on GitHub - Tracking the desktop applications in real-time and time spent on each application - Built a patch for this application to support the Linux environment

EDUCATION

Course Institution/

University

Year Marks

BE

(Telecommunication)

RV College of

Engineering, B’lore

2019 7.17/10

12th (PUC)

Vagdevi PU

College,

Bagalkot

2015 90.16%

10th (High School)

St Ann’s

Convent High

school,

Bagalkot

2013 91.36%

SKILLS

GOOD KNOWLEDGE OF:

OOP, Data Structures, Regex, Algorithms,

SQL, Linux commands, Git, debugging,

Statistics

Python: Numpy, Pandas, scikit-learn

Data visualization :

Matplotlib, seaborn, Plotly

ML/DL libraries familiar with:

Keras, PyTorch, fastai

IDE and Code Editors:

Visual Studio Code, Jupyter Notebook,

JupyterLab, Pycharm, Spyder

MS-Office:

Excel, OneNote, Word, PowerPoint

Operating Systems worked on:

Windows, Linux (Ubuntu)

CODING

Python - 4.5/5 (Passed: LinkedIn

Assessments)

C++- 4.5/5 (Passed: LinkedIn

Assessments)

C - 4/5

MATLAB/Octave - 3/5

Java - 3/5

Areas of Interest

Clustering

Auto ML

COMPETENCIES

Analytical Thinking & Problem Solving

Documentation

Multi-tasking

Curiosity

Quick Learner

CERTIFICATION/COURSES

Deep Learning - Specialization (Coursera)

[Offered by deeplearning.ai, taught by Andrew Ng]

- Consisted following of 5 courses

1. Neural Networks & Deep Learning

2. Improving Deep Networks: Hyperparameter tuning, Regularization, & Optimization

3. Structuring Machine Learning Projects

4. Convolutional Neural Networks

5. Sequence Models

Machine Learning (Coursera)

[Offered by Stanford, taught by Andrew Ng]

Python Programming (Udemy)

[Taught by Al Sweigart]

Advanced Data Science with IBM - Specialization

(Coursera) (Ongoing)

[Taught by top Data Scientists from IBM]

ADDITIONAL DETAILS

- Advanced Python programmer

- Good knowledge with some experience of building and distributing Python packages

- Other MOOCs undertaken: fast.ai - ML, DL

- Good Domain knowledge of Electronics and communication systems. LANGUAGES

English

Marathi

Hindi

Kannada

ACTIVITIES & HOBBIES

Chess

Playing Violin, Classical Music

Reading (Books, research papers, blogs)

Trading & Investing

Yoga, Meditation



Contact this candidate