Posts

Jupyter Notebook!! What is it?

The Jupyter Notebook  It is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. To install Jupyter notebook follow the steps below. first install python. Install the latest version. Python Then in the terminal or command line type: If its terminal then. its  sudo pip install jupyter notebook if its command line then.  pip install jupyter notebook The documentation for jupyter notebook is in this the below link: jupyter notebook Congratulation!! you have successfully installed jupyter notebook. From here on you have to install various packages for data science to get started with it, if you are working in python. click here.

numpy!! What is it..

numpy!! What is it.. If you are reading this then you are passionate about doing some data munging. Numpy is a fundamental python library used for scientific computation. It is used in Data anlaysis as well. It is the first step you need to take, of course,after collecting data is to use numpy for shaping the data. To download numpy use anaconda which is a most popular scientific package which contains all the necessary tools needed for data analysis. Anaconda OR you can take the other route of installing a particular package itself, to do so. first install python. Install the latest version. Python Then in the terminal or command line type: If its terminal then. its  sudo pip install numpy if its command line then.  pip install numpy The documentation for numpy is in this the below link: Numpy Congratulation!! you have successfully installed numpy & now you had taken the first step towards mastery of Data Science. The next step from here is to insta...

Git hub repo

I have uploaded some Data Science projects, Tutorials and Research at the following github repo.. https://github.com/11Satyendra11/Data_Science.git There is lot to come. Keep positive.