nitzmali Goto Github PK

andrewngcoursera

artificial-intelligence--path-planning-and-search-algorithms

This project is intended as an exploration of various search algorithms, both in the traditional application of path planning, and more abstractly in the construction and design of complex objects. We first generated Mazes and solved simple mazes using the classical search algorithms (BFS/DFS/A*). Once We have written these algorithms, we utilized other search algorithms like Local Beam Search to generate mazes that your initial algorithms have trouble solving.

artificial-intelligence-minesweeper

Takes Input for each cell which is a dictionary data structure used to expand its Knowledge base using intelligent tracking, constraint specification, logic and satisfiability.

big-data-project-on-udacity-forum-data-set-using-hadoop-map-reduce-in-python-

The focus was on to study the different co-relations and help in decision process related to student’s posting in forum. The huge data set exported from RDBMS and transferred whole data on Hadoop cluster. Map reduce codes were written in python in Unix OS.

bios8366

Advanced Statistical Computing at Vanderbilt University Medical Center's Department of Biostatistics

blogging-website-using-django-framework

Built a website Using Python and Django framework with the help of Bootstrap where i published my website on Heroku app using sql3 database server.

bmi_prediction

business-intelligence-and-big-data-analytics-for-walmart-using-excel-and-tableau

What predictive analytics does? It is the process of analysing historical data, understanding the present data, and using the connection between the historical data and the present data to infer what the future may be. So here in the given data set we will be analysing the past events to look for the insights on how to approach the future. We can analyse the trends or likelihood of a situation occurring. The techniques considered here are: * Predicting market trends. * Customer needs. * Creating customized offers for each segment channel and to predict changes in the demand and supply across the entire supply chain.

convert-gray-color-image-to-color

We divided the data into training, test and validation. We experimented with various hyperparamters in our case such as number of clusters, type of input (clustered, normalized, one hot encoded), type of output (cluster centers, one hot encoded), learning rate and worked on training and test data. Based on the results we quantified the tuning parameter in Linear regression so as to increase the accuracy as much as possible results on the validation data set.

data-visulization

database-management-project-for-hotel-management

Designed responsive and dynamic webpages (UI) using various front-end technologies/libraries (HTML, CSS, JavaScript, Bootstrap). Designed database for the system (SQL, MySQL server). Used Python Flask Framework for developing a web server. python, CGI at the backend. Django framework was also used for latest version. DBA tasks were performed using Python scripts to test the query and plotted graphs for performance.

genome-wide-association-studies-gwas-

To study the problem of Parkinson’s Disease we have the raw data from two experiments. We analyzed these experimental raw data and integrated the results. This publication describes a genome-wide association study on Parkinson's Disease. More than 408,000 single nucleotide polymorphisms (SNPs) were measured (or genotyped) across 276 patients with Parkinson’s Disease, and 276 normal control individuals. Each SNP is a potentially differing nucleotide between individuals. Recall that there are estimated to be as many as 10 million SNPs in the human genome, so this collection does not encompass all of them. So we identified top 10 SNP's based on this raw data.

health-beneficiaries-relocated-based-on-physicians

Led a team of 5 members to perform a complete data analysis process over the CMS healthcare dataset with over 2 million rows to help our client find a solution to his problem. Filtered and preprocessed the dataset based on our client requirements/features and diseases. Developed a Tableau dashboard, which explained all the visual/data/statistical analysis of various Health care providers across the USA. Narrowed down the dataset based on quality of provider’s services and their Medicare submitted charges. Finally, Performed Clustering algorithm using Rstudio to group the providers with similar features in order to recommend more affordable options for our client. Tools and Skills: Tableau Dashboards, Rstudio and stat-tools.

hr-analytics

The specific goal here is to predict whether an employee will stay or voluntary leave within the next year. In the present data, this means predicting the variable “vol_leave” (0 = stay, 1 = leave) using the other columns of data. You can think of this data as historical data which tells us who did and who did not leave within the last year. Our initial step is to describe and visualize our data. Then, we will develop two different kinds of predictive models. The first of these is a logistic regression model. Logistic regression models predict the likelihood of a categorical outcome, here staying or leaving.

image-classification-

Constructed a model to classify images as Class A or B, and trained it on the indicated data. Model is predicted for each of the unlabeled images. I used support vector machines and Logistic regression built from scratch in Python to classify the images.

job_transition_pathway

kaggle

machine_learning_practice

mlcourse.ai

Open Machine Learning Course

portfolio

practical-machine-learning-with-python

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

probabilistic-hunting

Developed a Probabilistic based search for a target in varying terrains, for both stationary and moving targets. The Maze was built using Numpy. This can be scaled to tracking terrorist movements or any lost packages in an inaccessible location. Built everything in Python 3 and Turtle.

python-tabulate

Pretty-print tabular data in Python, a library and a command-line utility. Repository migrated from bitbucket.org/astanin/python-tabulate.

seaborn-data

Data repository for seaborn examples

sklearn

tensorflow