Categories
Machine Learning

Expected to identify trends from social media data; From all the products available on Flipkart identify trending products, utilize all signals available (ex. posts, sessions, check-ins, social graphs, media content, etc.).

Expected to identify trends from social media data; From all the
products available on Flipkart identify trending products, utilize all signals available (ex. posts, sessions,
check-ins, social graphs, media content, etc.). Output should also have photos, videos, gifs which can be
used on Flipkart app.Preferred tech: Open source
Bonus: Signal extraction from multiple social media channels (ex. FB, Instagram, Twitter, etc.)

Categories
Machine Learning

A friend has started college at ECPI University. Your friend saves her work on her desktop. Her desktop is becoming crowded. She cannot find the documents that she is looking for using her current method of saving everything to the desktop. You look at her desktop and cannot see the background image because it is full of documents. https://www.asianefficiency.com/organization/organ…

Scenario
A friend has started college at ECPI University. Your friend saves her work on her desktop. Her desktop is becoming crowded. She cannot find the documents that she is looking for using her current method of saving everything to the desktop. You look at her desktop and cannot see the background image because it is full of documents. https://www.asianefficiency.com/organization/organ…
How do you intend to set up a hierarchy of files and folders to improve file management with school-related files for your friend? Defend your decisions.
Response Format
Support your answers with at least one credible source. Please use the ECPI Online Library, and your textbook to conduct your research.
Use in-text citations and a reference list in your responses using APA format.
Your response should demonstrate critical thinking and provide justification.

Categories
Machine Learning

Create an LDA model of your own custom dataset. You can choose any documents you wish or you can just gather textual data on something you find interesting. This technique is great for extracting key ideas for a large set of text that you have not personally analyzed. Create your txt file(s) – choose the number of topics (2) 5 words per topic

Create an LDA model of your own custom dataset. You can choose any documents you wish or you can just gather textual data on something you find interesting. This technique is great for extracting key ideas for a large set of text that you have not personally analyzed. Create your txt file(s) – choose the number of topics (2) 5 words per topic
Set up your LDA code (LDA assigns each word randomly to a topic)
See what topics come out
Refine the LDAAdd new stop words
Adjust the number of topics
Repeat Steps 3 and 4 until happy with the results
Write a 1 page summary of the data and the topics extracts. Display the top X words per topic
***I am stuck and have provided screen shots of my code***