Machine learning and data science

Akshay Patel **/**/**** adfj2x@r.postjobfree.com https://www.linkedin.com/in/akshay-patel-1302/

Examination University Institute Year CPI / %

Graduation Shri Ramswaroop University Shri Ramswaroop University 2017 7.4 Intermediate ISC St. Dominic Savio College 2013 82.20 Matriculation ICSE St. Dominic Savio College 2011 77.75 WORK EXPERIENCE

Analytics Vidhya Content Writer [Jul,19-Present]

Writing blogs on medium.com, a well-known platform for publishing technical blogs.

Support Vector Machines - https://medium.com/analytics-vidhya/support-vector-machines-805a24507f

Logistic Regression- https://medium.com/me/stats/post/46a0f3cdecef Motor Sales Pvt Ltd. Lucknow Assistant Service Engineer [Sept,17- Dec,18]

Engaged in first-level support for customers requiring routine support and troubleshooting.

Analyzed and diagnosed Customer-related problems and provided prompt repair and solutions. ACADEMIC PROJECTS and INTERNSHIPS

AppliedAI Cousrse on Data Science and Machine Learning [Apr,19 -Present]

Car Dekho https://carresale.herokuapp.com/ [Aug,20 -Aug,20] Predicting the price of the used car using machine learning. Deployed using Flask and Heroku. Used Random ForestRegression as a baseline model.

Spam/Ham Detector [Aug,20 -Aug,20]

Predicting whether the mail is a Spam or Ham using machine learning. Deployed using Flask and AWS EC2 instance. Used Support Vector Machine as a baseline model. http://ec2-13-58-249-46.us-east-2.compute.amazonaws.com:8080/

Link Prediction [Aug,20 -Aug,20]

Based on the current network we want to be able to predict the upcoming changes in the network and make recommendations accordingly. Dataset is about 8GB. Regression problem and hence trained a RandomForestRegressor managed to get the F1-score of 92%

Taxi-Demand Prediction [Aug,20 -Aug,20]

Time-series forecasting and Regression problem to find number of pickups, given location coordinates (latitude and longitude) and time. Dataset is about 6-8GB. Trained two different models RandomForest and XGboost regression and managed to get the mean average percentage error of 9%.

MNIST [Jul,20 -Jul,20]

Handwritten recognition using Convolutional Neural Network and Multilayer Perceptron. Dataset consisted of 60,000 data points in training, 10,000 points in test data. Received an accuracy of 99 %( CNN) and 98 %(MLP).

Quora Project [Jul,20 -Jul,20]

Quora Question Pair Similarity using Machine Learning. Data consisted of ~4lac points. By Feature Engineering results were improved and various models were built where XGBoost outperformed others with log-loss of 33%.

Cancer Diagnosis [Jul,20 -Jul,20]

Predicting cancer using Machine Learning. 3300 datapoints were taken in which ‘Text’ feature was the most important one. Models trained in Logistic Regression and SVMs were the best, having a log-loss of only 0.9%.

Donor’s Choose [Jun,20 -Jun,20]

Automation of the task of choosing projects for Donations using different algorithms like Naïve Bayes, KNN, XGBoost. Dataset consisted of 1lac points. Preprocessing of texts was done with other data analyses.

PUBG Project [Jun,20 -Jun,20]

Prediction of players rank on a PUBG dataset using machine learning and python. Preprocessing of data and Feature Engineering was performed. Ranking algorithm was used in order to rank the players.

Web Scrapping [Apr,20 -Apr,20]

Scraped and built notification alert on Coronavirus using Python and Beautiful Soup. Scraped mha.gov.in to get state-wise data on CoronaVirus Updates and displayed the desired State result in notification panel on Windows.

Sentiment Analysis [Jun,19 -Jun,19]

Prediction of the sentiment of reviews of Amazon Fine Food Review Dataset using machine learning. It involved loading the data from the database, cleaning it and data analysis and model building on it.

AI Assistant [May,19 -May,19]

Built an AI Assistant using Python and its modules like Speech Recognition, smtplib, pyttssx3. KPMG Internship on Data Analytics [Apr,20 -May,20] Worked on Data Quality Assessment, Data Insights and Data Presentation. Generated leads on which state and which particular customers to target to increase the sale. Shri Ramswaroop Memorial University Major Project [Sept,16 -Feb,17] Traffic Intensity Lighting System: Controlling traffic lights based on intensity of traffic using Arduino. CETPA InfoTech Private Ltd., Lucknow Minor Projects [Jun,16 -Aug,16] Controlling led lights using AVR16 microcontroller and C-Programming. TECHNICAL STRENGTHS

Languages Python for Data Science, SQL, HTML, CSS, JavaScript, C# for Unity, MATLAB Software & Tools VS Code, Unity Game Engine, Microsoft PowerBI AREAS OF INTEREST

Game Development, Designing Chatbots using NLP and DL, Coding CERTIFICATIONS

Cutshort Certified: Python-Basic, JavaScript-Basic, Data Science-Basic, Hackerrank: Python Basic 2020 Mastering the art of Data Visualization, Whatsapp Automation using Python 2020 EXTRA-CURRICULARS

Runners-up in Inter-Faculty Cricket and Football Tournament 2017, 2016, 2014 Participated in Inter-University Events and Won Gold and Silver medals at School level

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