In this part, I figured out several ways to present and create a Word Cloud using different methods — Tableau, Python, and Google World Cloud Generator.
Word Cloud is one of the data visualization tools for text data. One of my projects is to analyze the Amazon review data (the project link)and I applied Natural Language Processing and NLTK toolkits for EDA (Exploratory Data Analysis). In this part, I figured out several ways to present and create a Word Cloud using different methods — Tableau, Python, and Google World Cloud Generator.
I created this dataset myself and this dataset was a sample for my hard-coded chatbot project. If you are interested in my chatbot project please feel free to visit my GitHub repo. Let us take look at the data. This table has two columns- question and answer. And we can see that this data contains some punctuation and signs. The first thing we need to do is to pre-process this text data.
After data pre-processing with NLP, we get a list like this- Bag of words (BOW) and save it as a CSV file.
Mismanagement of multi-cloud expense costs an arm and leg to business and its management has become a major pain point. Here we break down some crucial tips to take some of the management challenges off your plate and help you optimize your cloud spend.
If you looking to learn about Google Cloud in depth or in general with or without any prior knowledge in cloud computing, then you should definitely check this quest out.
**Link: https://www.youtube.com/watch?v=gud65lqebrc** In this [**Google Cloud Training**](https://www.youtube.com/watch?v=gud65lqebrc "Google Cloud Training") live session, you will know everything about google cloud from basic to advance level...
What is Google Cloud? The Google cloud platform provides its users with stable and highly scalable cloud computing services. These services help customers compute and store information and help developers...
First Serverless compute service by Google Cloud.Google Cloud has always believed in the vision of serverless by debuting with Google App Engine in 2008, the first fully serverless compute service. Since then, Google has evolved more serverless offerings in both application development and analytics. I started working in Google App Engine in May 2017 and I am going to share my experience with GAE.