Pinned Repositories
Classify-Song-Genres-from-Audio-Data
Using a dataset comprised of songs of two music genres (Hip-Hop and Rock), you will train a classifier to distinguish between the two genres based only on track information derived from Echonest (now part of Spotify). You will first make use of pandas and seaborn packages in Python for subsetting the data, aggregating information, and creating plots when exploring the data for obvious trends or factors you should be aware of when doing machine learning. Next, you will use the scikit-learn package to predict whether you can correctly classify a song's genre based on features such as danceability, energy, acousticness, tempo, etc. You will go over implementations of common algorithms such as PCA, logistic regression, decision trees, and so forth
Dr.-Semmelweis-and-the-Discovery-of-Handwashing
In 1847 the Hungarian physician Ignaz Semmelweis makes a breakthough discovery: He discovers handwashing. Contaminated hands was a major cause of childbed fever and by enforcing handwashing at his hospital he saved hundreds of lives. In this python project we will reanalyze the medical data Semmelweis collected
Exploring-67-years-of-LEGO
The Rebrickable database includes data on every LEGO set that ever been sold; the names of the sets, what bricks they contain, what color the bricks are, etc. It might be small bricks, but this is big data! In this project, you will get to explore the Rebrickable database. To do this you need to know your way around pandas dataframes and it's recommended that you take a look at the courses pandas Foundations and Manipulating DataFrames with pandas.
Exploring-the-Bitcoin-cryptocurrency-market
To better understand the growth and impact of Bitcoin and other cryptocurrencies you will, in this project, explore the market capitalization of different cryptocurrencies.
Exploring-the-evolution-of-Linux
Version control repositories like CVS, Subversion or Git store rich evolution information about a software project. In this project, you'll be challenged to read in, clean up and visualize a real world Git repository dataset of the Linux kernel. With almost 700k commits and thousands of contributors (find out the exact number in this project ;-) ) there are some little data cleaning and wrangling challenges that you'll encounter. But you'll also gain insights about the development activities over the last 13 years. For this Project, you need to be familiar with Pandas DataFrames, especially the read_csv and groupby functions, as well as with working with time series data. You can learn the required skills in these courses: Intermediate Python for Data Science pandas Foundations
Lab_task1
Node_coursera
Repository for assignment of node course on coursera.
pandas_exercises
Practice your pandas skills!
python-test
Semantic-UI-React
The official Semantic-UI-React integration
Augadh1's Repositories
Augadh1/Classify-Song-Genres-from-Audio-Data
Using a dataset comprised of songs of two music genres (Hip-Hop and Rock), you will train a classifier to distinguish between the two genres based only on track information derived from Echonest (now part of Spotify). You will first make use of pandas and seaborn packages in Python for subsetting the data, aggregating information, and creating plots when exploring the data for obvious trends or factors you should be aware of when doing machine learning. Next, you will use the scikit-learn package to predict whether you can correctly classify a song's genre based on features such as danceability, energy, acousticness, tempo, etc. You will go over implementations of common algorithms such as PCA, logistic regression, decision trees, and so forth
Augadh1/Dr.-Semmelweis-and-the-Discovery-of-Handwashing
In 1847 the Hungarian physician Ignaz Semmelweis makes a breakthough discovery: He discovers handwashing. Contaminated hands was a major cause of childbed fever and by enforcing handwashing at his hospital he saved hundreds of lives. In this python project we will reanalyze the medical data Semmelweis collected
Augadh1/Exploring-67-years-of-LEGO
The Rebrickable database includes data on every LEGO set that ever been sold; the names of the sets, what bricks they contain, what color the bricks are, etc. It might be small bricks, but this is big data! In this project, you will get to explore the Rebrickable database. To do this you need to know your way around pandas dataframes and it's recommended that you take a look at the courses pandas Foundations and Manipulating DataFrames with pandas.
Augadh1/Exploring-the-Bitcoin-cryptocurrency-market
To better understand the growth and impact of Bitcoin and other cryptocurrencies you will, in this project, explore the market capitalization of different cryptocurrencies.
Augadh1/Exploring-the-evolution-of-Linux
Version control repositories like CVS, Subversion or Git store rich evolution information about a software project. In this project, you'll be challenged to read in, clean up and visualize a real world Git repository dataset of the Linux kernel. With almost 700k commits and thousands of contributors (find out the exact number in this project ;-) ) there are some little data cleaning and wrangling challenges that you'll encounter. But you'll also gain insights about the development activities over the last 13 years. For this Project, you need to be familiar with Pandas DataFrames, especially the read_csv and groupby functions, as well as with working with time series data. You can learn the required skills in these courses: Intermediate Python for Data Science pandas Foundations
Augadh1/Lab_task1
Augadh1/Node_coursera
Repository for assignment of node course on coursera.
Augadh1/pandas_exercises
Practice your pandas skills!
Augadh1/python-test
Augadh1/Semantic-UI-React
The official Semantic-UI-React integration
Augadh1/startbootstrap
Augadh1/Survey
For this project we will be exploring data from Developers’ Survey done by stackoverflow.com every year. This data is huge consisting of around 1 lac developers’ world-wide and on multiple factors. As part of this DataSet there are two files - survey_results_schema.csv – It contains list of all the columns and their description survey_results_public.csv – It contains the Survey data corresponding to different columns
Augadh1/temp
Augadh1/testproject
Augadh1/tutorbin
Augadh1/v
Augadh1/vending
Augadh1/vending-machine