en
Feedback
Epython Lab

Epython Lab

Open in Telegram

Welcome to Epython Lab, where you can get resources to learn, one-on-one trainings on machine learning, business analytics, and Python, and solutions for business problems. Buy ads: https://telega.io/c/epythonlab

Show more
6 194
Subscribers
-624 hours
-227 days
-6530 days
Posts Archive
Artificial Intelligence, IOT and machine Learning : AI programs using Python A Beginners book @epythonlab #AIbooks

Function Parameters Vs Arguments in Python https://youtu.be/WiJMTC7n6XE

Share and invite your friends to the channel @epythonlab

Upcoming videos... 1. Scrapping others Telegram groups members 2. Adding scraped members into your own group I wanna know your reaction?

I found a github repo it might be helped you https://github.com/epythonlab/

AI for Data Science #AIbooks @epythonlab

How to run Jupyter Notebook on Visual studio code https://youtu.be/-uJRlXDhrZI4

LEARN PYTHON FROM SCRATCH #Subscribe and #Share https://youtu.be/1VT9VaQn-q4

What is the output of the following code x = 2 def square(): global x x= 4 res = (x**2) * x return res print(square())
Anonymous voting

My plan is to prepare data science notes and workshops via YouTube and Zoom.

Function Scope: Global or Local https://www.youtube.com/watch?v=GzbPCRcf-gU

#nlp #ml @epythonlab
#nlp #ml @epythonlab

#nlp #ml @epythonlab
#nlp #ml @epythonlab

ML Algorithms Cheatsheet (python and R) #code #python #R @epythonlab #mlbooks

Watch "Python Tutorial Part-09| Function Definition in Python" on YouTube https://youtu.be/5IHXsnxdVFI

spaCy is a Python package that bills itself as "industrial-strength" natural language processing. https://spacy.io/

#Keynote #DataScience #NLP #Python @epythonlab Natural Language Processing Natural language processing (NLP) is the field devoted to methods and algorithms for processing human (natural) languages for computers. NLP is a vast discipline that is actively being researched. Some examples of machine learning applications using NLP include sentiment analysis, topic modeling, and language translation. In NLP, the following terms have specific meanings: - Corpus: The body/collection of text being investigated. - Document: The unit of analysis, what is considered a single observation. Examples of corpora include a collection of reviews and tweets, the text of the Iliad, and Wikipedia articles. Documents can be whatever you decided, it is what your model will consider an observation. For the example when the corpus is a collection of reviews or tweets, it is logical to make the document a single review or tweet. For the example of the text of the Iliad, we can set the document size to a sentence or a paragraph. The choice of document size will be influenced by the size of our corpus. If it is large, it may make sense to call each paragraph a document. As is usually the case, some design choices that need to be made.