Epython Lab

Mathematics for Machine Learning RoadMap 🔗 Link to Linear Regression https://bit.ly/46rqiBu 🔗 Link to Linear Algebra https://bit.ly/45EpfwB 🔗 Link to Probability Distribution https://bit.ly/495L8b5 🔗 Link to Telegram Group https://bit.ly/3IR1lnm

INTRODUCTION TO PROBABILITY DISTRIBUTION FOR MACHINE LEARNING WITH PYTHON 1. What is a random variable? 👉🏿 https://youtu.be/TkFipAuH-rY 2. Types of a random variable 👉🏿 https://youtu.be/jBYsKZOxR6k 3. Calculating probability using probability mass function 👉🏿 https://youtu.be/ceSvPxY_uAk 4. Calculating probability over a range 👉🏿 https://youtu.be/_WF9X4RyARA 5. Calculating Probability using the cumulative distribution function 👉🏿 https://youtu.be/tfoGiPlwiys 6. Calculating probability of continuous variable using density function and cumulative distribution function    👉🏿 https://www.youtube.com/watch?v=ikete4WQaj0

Machine Learning Terminology Bag of words: A technique used to extract features from the text. It counts how many times a word appears in a document (corpus), and then transforms that information into a dataset. https://youtu.be/tn-Tvi8CHmg

Data Structures with Projects full tutorial for beginners https://www.youtube.com/watch?v=lbdKQI8Jsok #share this post Join #epythonlab https://t.me/epythonlab

As a programmer, you must know the concept of object oriented programming. Here you go https://www.youtube.com/watch?v=I7z6i1QTdsw

In this topic modeling project-based tutorial, I have gone through the following steps: 1. Loads the documents(Generating sample documents) 2. Preprocesses the text by removing stop words and stemming words. 3. Creates a TF-IDF vector representation of the documents. 4. Performs LDA topic modeling with the specified number of topics. 5. Extracts the document-topic weight matrix. 6. Prepares the data for CSV format, including document IDs and topic weights. 7. Saves the results to the specified CSV file. https://youtu.be/uJCB2hRCB60

Join my channel as a member https://www.youtube.com/channel/UCsFz0IGS9qFcwrh7a91juPg/join

By transforming our DataFrame into XML, we ensure that our data remains structured and readable across different platforms and applications. Step by step guide: https://youtu.be/wNKKrt885xY

Mojo Programming Language - Full Course for Beginners https://youtu.be/pyfCTxKcDPY Join #epythonlab https://t.me/epythonlab

I'm curious🤭 about statistics Vs Probability Here, I have made some tutorials about probability distribution for Machine learning using Scipy Python library https://www.youtube.com/playlist?list=PL0nX4ZoMtjYEl_1ONxAZHu65DPCQcsHmI

Creating and parsing XML documents in Python is a valuable skill for managing and exchanging structured data. In this tutorial, I'll cover the basics of creating XML documents and parsing them using Python's built-in XML module. https://www.youtube.com/watch?v=WnbS90EzU0Y

Who's here?  We've asked for a free link to a paid channel, for our subs. x2-x3 Signals here 👉 CLICK HERE TO JOIN 👈 👉 CLICK HERE TO JOIN 👈 👉 CLICK HERE TO JOIN 👈 ❗️JOIN FAST! FIRST 1000 SUBS WILL BE ACCEPTED

If you are facing challenges of parsing and transforming nested XML document into a user friendly pandas DataFrame, this tutorial is for you. Please 🙏 Like, Share and comment any words you feel about this tutorial. Thanks for your support. https://youtu.be/WQ-OhoXmHU8

Who's here?  We've asked for a free link to a paid channel, for our subs. x2-x3 Signals here 👉 CLICK HERE TO JOIN 👈 👉 CLICK HERE TO JOIN 👈 👉 CLICK HERE TO JOIN 👈 ❗️JOIN FAST! FIRST 1000 SUBS WILL BE ACCEPTED

Creating and parsing XML documents in Python is a valuable skill for managing and exchanging structured data. In this tutorial, I'll cover the basics of creating XML documents and parsing them using Python's built-in XML module. learn here

In Pandas, how do you select a single column from a DataFrame? Comment your answer ✅ Join #epythonlab https://t.me/epythonlab

What is Pandas? Pandas is an open source library, providing high-performance, easy-to-use data structures and data analysis tools for Python. The DataFrame is one of Pandas' most important data structures. It's basically a way to store tabular data where you can label the rows and the columns. One way to build a DataFrame is from a dictionary and also importing from CSV(comma-separated value). Here are the most common pandas functions for data analysis https://youtu.be/8a3Y-HT09sQ #KeyNote #Pandas #DataFrame #DataScience

Object oriented Programming is an important concept that must be known by all computer coders. https://www.youtube.com/watch?v=I7z6i1QTdsw Join #epythonlab https://t.me/epythonlab

What is the output of the above code? Comment your answer. Join #epythonlab Https://t.me/epythonlab