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Ahmad Varasteh
Italy
Приєднався 24 вер 2014
Hello, I'm Ahmad Varasteh, a data scientist with a passion for data visualization and algorithms. My journey in the world of data analytics has been enriched by my background in software engineering, enabling me to seamlessly apply my data science knowledge to develop innovative software products. As a data scientist, I thrive on unearthing valuable insights from complex datasets and leveraging them to make informed decisions. Beyond my professional pursuits, teaching is a fulfilling hobby that allows me to share my expertise and empower others. During my leisure time, you can often find me immersed in the world of video games, where I channel my creativity and strategic thinking. With a Master's degree in data science, I am well-equipped to tackle challenging analytical problems and make a positive impact in both the data and software realms.
Data Scenario #1: Building an E-Commerce Product Recommendation System with RAG and OpenAI
Welcome to the first episode of the Data Scenario series! 🎉
In this video, we step into the shoes of an AI Engineer at ShopVista, a leading e-commerce platform aiming to revolutionize its product recommendation system. Our goal is to develop a context-driven search feature that provides personalized product suggestions based on users' search phrases.
What we'll cover:
Understanding the Scenario: Dive deep into the real-world challenge presented by ShopVista.
Dataset Exploration: Analyze the provided dataset containing product titles, descriptions, and identifiers.
Introduction to RAG Systems: Learn about Retrieval-Augmented Generation and how it enhances recommendation systems.
Implementing OpenAI Models: Utilize OpenAI's powerful models to understand user intent and generate relevant suggestions.
Building the Recommendation System: Step-by-step coding tutorial to create a functional, AI-driven recommendation engine.
Testing and Evaluation: Ensure our system delivers intuitive and tailored recommendations to enhance user experience.
Why watch this video?
By the end of this tutorial, you'll have hands-on experience building an advanced recommendation system using state-of-the-art AI techniques. This skill is valuable for any data professional looking to solve complex problems in the industry.
🔗 Resources:
To get started with this data scenario, download the project resource file from the following link:
- GitHub Repository: github.com/ahmadvh/Data-Scenario
- Check out other scenarios: ua-cam.com/play/PLgYONms4SxY3lkSrcN3Q9YoVCyLXuHkrT.html
In this video, we step into the shoes of an AI Engineer at ShopVista, a leading e-commerce platform aiming to revolutionize its product recommendation system. Our goal is to develop a context-driven search feature that provides personalized product suggestions based on users' search phrases.
What we'll cover:
Understanding the Scenario: Dive deep into the real-world challenge presented by ShopVista.
Dataset Exploration: Analyze the provided dataset containing product titles, descriptions, and identifiers.
Introduction to RAG Systems: Learn about Retrieval-Augmented Generation and how it enhances recommendation systems.
Implementing OpenAI Models: Utilize OpenAI's powerful models to understand user intent and generate relevant suggestions.
Building the Recommendation System: Step-by-step coding tutorial to create a functional, AI-driven recommendation engine.
Testing and Evaluation: Ensure our system delivers intuitive and tailored recommendations to enhance user experience.
Why watch this video?
By the end of this tutorial, you'll have hands-on experience building an advanced recommendation system using state-of-the-art AI techniques. This skill is valuable for any data professional looking to solve complex problems in the industry.
🔗 Resources:
To get started with this data scenario, download the project resource file from the following link:
- GitHub Repository: github.com/ahmadvh/Data-Scenario
- Check out other scenarios: ua-cam.com/play/PLgYONms4SxY3lkSrcN3Q9YoVCyLXuHkrT.html
Переглядів: 105
Відео
Non-Negative Matrix Factorization (NMF) | Multiplicative Update Rules By Lee And Seung
Переглядів 41 тис.4 роки тому
NMF Algorithm Non-negative Matrix Factorization (NMF) is a family of linear algebra algorithms used to uncover latent structures in data represented as a non-negative matrix. Input: Matrix X, rank k Output: Two k-dimensional factors W and H, which approximate X In this video, I demonstrate the use of the Multiplicative Update Method introduced by Lee and Seung (1999) to factorize the input matr...
OBJECT-ORIENTED PROGRAMMING | OOP in PYTHON
Переглядів 4104 роки тому
So in this video I'm going to explain what is Object-oriented Programming with a simple example in python. #object_oriented #python #object
CORONA VIRUS DATA SCIENCE POINT OF VIEW | COVID-19 DATA ANALYSIS
Переглядів 7394 роки тому
As a retro virus, SARS-CoV-2 has caused a fully grown pandemic, infecting more than 200 thousand people as of 18th March regardless of their nationalities. As data enthusiasts it is our common interest to make data into information by connecting the dots and filter the truth from the pile of hazardous information. If we fail to do so, the misinformation regardless of its’ sources will harm not ...
EXTRACTING NUMERICAL values from Strings | Python Tricks
Переглядів 7 тис.4 роки тому
in this video we are going to talk about how we extract numerical values from a string, using #regular_expressions in python. #re #python #regex
LIST COMPREHENSION FILTERING EXPLAINED | python tricks
Переглядів 854 роки тому
#LIST_COMPREHENSION #filtering #python_tricks #PYTHON
List Comprehension - Explained
Переглядів 464 роки тому
#list_coprehension #python #python_tricks Understanding list Comprehension
LIST COMPREHENSION python - EXPLAINED WITH EXAMPLE
Переглядів 1274 роки тому
in this video I am going to talk about what exactly happens in #List #Comprehension in #python.
Python EXECUTE | PYTHON TRICKS
Переглядів 834 роки тому
you can run python codes which is in a string using exec() built-in Method in #python.
HOW to LEARN PYTHON
Переглядів 1384 роки тому
#Python_as_your_first_language #Algorithmic_thinking #python WELLCOME TO THIS COURSE : PYTHON TUTORIAL for BEGINNERS in this series of videos we are going to talk about how to become a programmer from zero to hero. there are two steps to learn programming : 1 - learn how a computer thinks we call it (ALGORITHMIC THINKING) 2- learn python programming language we are going through each of these s...
TRANSLATOR IN PYTHON | GOOGLETRANS MODULE in PYTHON | VAFA NAPOLI !!!
Переглядів 7134 роки тому
#Joey_tribiani #vafa_napoli #Python make translator in python: In this video we are going to make a #translator using #python. we are going to use #googletrans module in python.
Python Tricks | Convert Data type of Elements In a list using Map Function
Переглядів 2564 роки тому
#map_function #python In this video we are going to talk about how to #Convert #Datatype of Elements In a list using Map Function.
PYTHON METHODS | LEARN WITH EXAMPLES !! USEFUL METHODS !!!
Переглядів 1084 роки тому
#data_science #jupyter_notebook #methods In this video we are going to talk about some of built-in methods in #python: - type() - int() , float() str() - max(), min() - abs() - sum() - round() - pow() - len() Explore more on Udemy: Join my course on e-commerce product recommendation systems using RAG: www.udemy.com/course/e-commerce-product-recommendation-rag-systems/
Installing JUPYTER NOTEBOOK using PIP
Переглядів 53 тис.4 роки тому
In this video we're going to talk about How to Installing Jupyter Notebook on windows 10 using PIP in three steps : 1- install python : www.python.org/ 2- install pip : pip.pypa.io/en/stable/installing/ 3- install jupyter notebook #pip #jupyter #data_science Explore more on Udemy: Join my course on e-commerce product recommendation systems using RAG: www.udemy.com/course/e-commerce-product-reco...
how to REVERSE a LIST in PYTHON - PYTHON TRICKS
Переглядів 854 роки тому
In this video we are going to talk about Two ways to Reverse a List in python. #python_lists #reversed_function #free_teaching
TEXT TO SPEECH USING PYTHON | TOO EASY !!
Переглядів 1 тис.4 роки тому
TEXT TO SPEECH USING PYTHON | TOO EASY !!
Convert Colored Image to Black and White in python | PIL module
Переглядів 3,5 тис.4 роки тому
Convert Colored Image to Black and White in python | PIL module
Most Frequent Element in a List Python - Collection Module
Переглядів 5034 роки тому
Most Frequent Element in a List Python - Collection Module
Python Tricks - LEARN ENUMERATE METHOD: Accessing indices of elements in a list
Переглядів 1444 роки тому
Python Tricks - LEARN ENUMERATE METHOD: Accessing indices of elements in a list
Python tricks - Split a word into Letters in Python
Переглядів 6 тис.4 роки тому
Python tricks - Split a word into Letters in Python
How to Spell a number in Python | inflect module
Переглядів 1,1 тис.4 роки тому
How to Spell a number in Python | inflect module
Append vs Extend | Methods in Python Lists
Переглядів 1384 роки тому
Append vs Extend | Methods in Python Lists
Python Tricks - Lambda expression | Lambda Function in Python
Переглядів 524 роки тому
Python Tricks - Lambda expression | Lambda Function in Python
convert two lists into a dictionary in Python
Переглядів 4714 роки тому
convert two lists into a dictionary in Python
Python Tricks - List Comprehension combined with if else statement
Переглядів 1044 роки тому
Python Tricks - List Comprehension combined with if else statement
Very informative.
Glad you think so!
So usefully ❤❤
So glad!
Well done ❤
Thanks 🙏
Github?
Hi, Thanks for the comment. Here is the link to the GitHub repo github.com/ahmadvh/Non-Negative-Matrix-factorization---Implemented-in-python
The background music is so enjoyable what's the track !?
This video is 4 years old and I actually don't remember the name of the track. If you find it please also let me know.
3632 Emmerich Cove
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Explaination not useful for a beginner
Sorry to hear that
This video was the what I need, subbed! (I'm the 666th sub)
Been trying to understand the list comprehension for 2 weeks until I saw this video. You are my G king
Glad to hear it
i was facing dificulty to install jupyter notebook your video is helpfull for me thank you sir ..
Glad it helped
after the command pip jupyter notebook, requirment already satisfied option comes, but after that when i type jupyter notebook, it says jupyter is not recognosed as an internal or external command. Plz help
having same issue
Thanks a lot you help my daughter
jupyter is not recognised as internal or external command what do i do next please respond
what does "not always positive semi-definite" mean and how it is related to solvability of the equation? Is there a nice video/website that anyone can recommend for it?
bro helped alot seriously
Thanks a million times sir
hi. what if words are in a column and i want to do whole column (pandas)
mersi ahmad joon ;))
how can i find only certain numbers, say i want to know only the number of apples i don't care about oranges
which location will it be stored in ?
cd Desktop cmd is showing the system can not find the path specific
What is the advantage of non-negative matrix factorization over matrix factorization without the constraint?
NMF does not allow negative entries in the matrix factors W and H. Unlike other factorization methods, these non-negativity constraints permit the combination of multiple basis images to represent the actual column of the original data. But Pascal, notice that this will cause only additive combinations because the non-zero elements of W and H are all positive and no subtractions can occur. For these reasons, the non-negativity constraints are compatible with the intuitive notion of combining parts to form a whole, which is how NMF learns a parts-based representation. For example, if each column of the datamatrix represent an facial image, then the basis matrix columns are features such as face mouth lips etc. while the column of H represents one to one correspondence with X. The columns of H indicate which feature is present in which image and with how much impact. So intuitively NMF "ADD" objects to recreate the observed data
Generally features learned this way are much easier interpretable
Very cool video.. Just a doubt on how do we choose K ?
I can't down load get-pip.py plz tell any other method to install
👍
Gotta love the idubbbz theme
When i write cd desktop on cmd, it stated "system cannot find the path specified" ?? I saved the target in desktop
It is good video for the beginner's. Thanks
2:20 I know this learning rates lead to multiplicative update rules and guarantee non-negativity, but would it be possible that the learning rates are too large at some iteration to guarantee the convergence of NMF?
it's not working in my case , it's still giving output as 1 word . :(
Man u r amazing. Was worrying like hell and skip today's class cz i was facing difficulty in installing jupyter notebook. Thank you so much.
Thank you so much
It really worked ...Thanks..
Great job, tks
After extracting numbers.. I have to rearrange them in string in a decreasing order.. How to do that.. Input: 3times4 is 12 Output:12times4 is 3 Input:Exam35 is Endby23 tomorrow98 Output: Exam98 is Endby35 tomorrow23 Output: Exam98 is
Great explanation!
Honestly the best explanation I've ever come across of object oriented programming
Sir thanks a lot but sir doubt how to install all packages?
Thank you !
hello. i was not able to check my version in cmd. im getting the response that python is not recognized as an internal or external command, operable program or batch file...pls help
uninstall python. While installing python, make sure that you have checked the checkbox "Add python to Environment variables".
@@ahmadvarasteh641 thank you
I would prefer to install it in python folder ... and you got pip for the desktop , i dont know if that can make some issues in the future ... thanks for the video
the best tutorial on this topic. u are very talented
pls make more video
Thanks man you helped me
hey. thanks for the tutorial.how to do the similar with video? is it possible?
parchamet balast <3
How to remove numbers and print only alphabets?
If you want to remove the numbers from the text, add this after the code of Ahmad Varasteh: # remove the numbers taken from the string in the string for number in numbers: text = text.replace(number, "") # replace double spaces with a single space text = text.replace(" ", " ") # show the manipulated string print(text) if you want to remove numbers from a string in general, do this (after the code of this video): # declare a list of numbers saved as chars all_numbers = ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"] # iterate every single char of the string # the numbers above are declared as chars, because "for char in text": char is a char type var for char in text: # if the char is a number, remove it if char in all_numbers: text = text.replace(char, "") # replace double spaces with a single space text = text.replace(" ", " ") # show the manipulated string print(text)