geetharamson Goto Github PK

Hi there 👋 from Geetha

About me:

• 🌱 I’m currently a student doing Higher Diploma in Business System Analytics in Waterford Insitute of Technology.

• 🤔 I’m starting the role of Associate Software Engineer

• 📫 How to reach me: [email protected]

  class geetha:
  
    def __init__(self):
       self.username = 'geetharamson'
       self.name = 'Geetha Karthikesan'
       self.current = 'Associate Software Engineer'
       self.parttime = 'Business Systems Analysis Student'
       self.university = 'Waterford Institute of Technology'
       self.studies = 'Bachelors in Engineering'
       self.pasteducation = 'Cochin University,Kerala,India'
       self.past = 'Data Analytics Graduate'
       self.pasteducation = 'Galway-Mayo Institute of Technology'
       self.email = '[email protected]'
       self.nationality = 'Irish'
       self.country = 'Ireland'
       self.livein = 'Co.Kildare'
       self.town = 'Maynooth'
       self.languages = 'English,Hindi,Tamil,Malayalam,very little knowledge of French,German,Dutch,Telugu and Chinese'
       self.englishlevel = 'Very Fluent'
       self.hobbies = 'Cooking and Gardening'
       self.job = 'Looking for an internship or work placement'
       self.skills = {'soft': ['Multitasking','Teamwork','Communication','Adaptability','Eagerness to learn'],
  'technical': ['React','HTML','CSS','JavaScript','MySQL','MongoDB','Numpy','Pandas','Seaborn','Matplotlib','Python']
       }
       
    def __str__(self):
        return self.name
  if __name__ == '__main__':
       me = geetha()
  

Here are some of the repositories of projects I did on this course of Higher Diploma in Computing and Data Analytics programme in GMIT.

Machine Learning Tasks-2020 Had to do four different taks. 1)Write a Python function called sqrt2 that calculates and prints to the screen the square root of 2 to 100 decimal places. 2) Use scipy.stats to verify the Chi-Squared test for independence is a statistical hypothesis test like a t-test value and calculate the associated p value. 3)Microsoft Excel has two different versions of the standard deviation as STDDEV.P and STDDEV.S. The STDDEV.P function performs the calculation using numpy as np.sqrt(np.sum((x - np.mean(x))** 2)/len(x)) but in the STDDEV.S calculation the division is by len(x)-1 rather than len(x). 4)Use scikit-learn to apply k-means clustering to Fisher’s famous Iris data set.

MachineLearning and Statistics-2020 A Flask web app that uses machine learning models to make predictions for the power output from wind turbines based on their wind speed values.

Big Data Representation-2020 A Flask web app with REST API. CRUD operations on a MySQL database.

Applied Databases-2020 CRUD operations on a relational database (MySQL) and a non-relational database (MongoDB) with a user interface to the databases using Python. A discussion on normalisation.

Web Application Development-2019A gym website using HTML5, CSS, JavaScript and the JavaScript library D3 for some basic data visualisations. Linked pages and user login.

Programming for Data Analysis Simulation-2019 Simulating Boston dataset using Python's numpy.random module.

Programming for Data Analysis Random Numbers Project 2019 Explaining the overall use of Python’s numpy. random package and in particular the use of its simple random data functions, permutations functions and distributions functions as well as the use of seeds in generating pseudorandom numbers.

Programming and Scripting-2019 Researching Fisher's Iris dataset and exploratory data analysis of the dataset using the Python data science stack.

Programming and Scripting Tasks2019 A set of ten programming problems aimed at learning core Python skills including input and output from the command line, handling exceptions, dates and times, writing functions and control flow in Python, string methods, reading and writing files and basic plotting using Matplotlib.

Fundamentals in Data AnalyticsData visualization plays an important role to explore and understand the data. Dataset used is Tips.Exploratory data analysis and regression analysis of the Tips dataset using the Python data science stack.