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gauravvermaji's Projects

a-2017

Public Repository for cs109a, 2017 edition

data-analysis-and-machine-learning-projects

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

feature-engineering-and-feature-selection

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

feature-selection-for-machine-learning

Methods with examples for Feature Selection during Pre-processing in Machine Learning.

flight-delay-prediction-project

This project is about flight delay and taken from kaggle

image-super-resolution

🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

introduction_to_ml_with_python

Notebooks and code for the book "Introduction to Machine Learning with Python"

jupyter

Jupyter metapackage for installation, docs and chat

machine-learning

Content for Udacity's Machine Learning curriculum

pandas-pipelines-custom-transformers

Material for Talk at PyData Seattle 2017

python-and-spark-for-big-data-master

Code along with the course 'Spark and Python for Big Data with PySpark' on Udemy

python_data_science_and_machine_learning_bootcamp

Jupyter notebook for Udemy course: Python data science and machine learning bootcamp

scientific-python-lectures

Lectures on scientific computing with python, as IPython notebooks.

whale-optimizer-for-partitoned-hwsn

The problem of network partition in ad-hoc networks received attention in the recent years. Many solutions have been proposed such as algorithms based, heuristics based, approximations based and meta-heuristic based to place additional relay nodes in partitioned heterogeneous wireless sensor networks to resume its operation. However, placing additional relay nodes in the partitioned network is shown an NP-Hard problem, because locations for relay node placements are not known in advance. Meta-heuristics are proven best-suited solutions to solve such kind of NP-Hard problem as well as optimization problem due to their problem independent and stochastic nature. In this research paper, we have introduced a network partition problem and developed a new nature inspired solution called Whale Optimizer to Repair Partitioned Heterogeneous wireless sensor networks (WORPH) based on the social behaviour of whales in the nature. In the proposed solution, a whale tries to find the optimal locations for attacking its prey. We have mimicked the said behaviour of whales in our proposed solution while considering the initial locations of deployed RNs inside disjoint partitions. The observed optimal positions are being used to find the optimal locations for deploying new RNs in such a way that partitioned network is restored in an optimal way. The simulation results are observed and compared with state-of-the-art approaches to prove the effectiveness of our proposed solution.

windrose

A Python Matplotlib, Numpy library to manage wind data, draw windrose (also known as a polar rose plot), draw probability density function and fit Weibull distribution

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