https://www.facebook.com/100388706385938/

Ikramullah Naqvi., Skardu (2024)

21/02/2024

CONFUSION MATRIX:
Noted:
Our desired prediction is Covid+
Actual value is Covid+ and model predicts Covid+... So called TP

Actual value is Covid + and model predicts Covid- so called FN... false es lea q ki model na ghalat prediction ki or negative es lea q ki Covid - is not our desired prediction....

Actual value is Covid- and model predicts Covid+ FP .... False es lea q ki model predicts wrong that is Covid+ but positive es lea q ki model predicts Covid+ which is our desired prediction..

Actual value is Covid- and model predicts Covid- ....

21/02/2024

Under fitting:
Training and testing accuracy are low....
May b algorithm is very simple for example k-N ... Eska real life example ye hoga... For example kal Apki english ka exam ha or poems book ma poem ki last ma summary likhi hoti ha ap wai parh k jain gy or agr exam ma details ma question ay to ap uski answer ni kr pao gy q ki ap na to sirf summary Parh li thi yaani algorithms ya data set Apki boht kam thy...
If you are using neural network then add multiple layers if you are using random forest add more decision tress,, if using decision tree then increase depth of decision tree eska mtlb yai ha ap apny algorithms ko complex karen

21/02/2024

Over fitting:
It's called Ratta , Usi data pa jo yaad Ki hoti ha 💯 percent accuracy ay gi , when someone aks questions from those questions jo us na yaad ni ki Hoti to fans geya .... Mera 1 dost tha FSC ma wo mathematics k saray questions yaad krty thy , fr hamen aksar questions examples ma sa i to fail ho geya 😁 mtlb wo over fitting hva hva tha .... Sir Irfan Malik explain Ai with very easy way with joyful examples to hamen Sir ki smj Aati he lekin kahin or Ai prhny laga to uski smj ni aati to ye b over fitting ha🤗...
Jab ham codes ChatGpt sa copy krny lagtay hen to ham khud sa codes Solve krny ki salaheyat kho jaati ha ye b over fitting ka example ho skti ha...

17/02/2024

کچھ بہن بھائیوں کو شکایت ہے کہ غزہ پر بات کرنے کی بجائے پاکستانی الیکشن پر کیوں نہیں بات کرتا۔

غزہ میں جہاد جاری ہے۔ جس علاقے اور جن جنگوں کی پیشگوئی اللہ کے رسول صلی اللہ علیہ وآلہ وسلم نے کی تھی، ان پر بات کرنا فرض ہے۔

رہی بات پاکستانی سیاست کی تو اس میں ظلم اور مظلومیت مستقل فیچر ہیں، ظالم اور مظلوم آپس میں پوزیشن بدل لیتے ہیں۔ اس میں چیخیں مستقل ہیں، چیخنے والے آپس میں پوزیشن بدل لیتے ہیں۔ جس پارٹی کو لایا جائے، وہ خوش۔ جسے نہ آنے دیا جائے وہ مظلوم۔ اگلے الیکشن میں پوزیشنیں پھر بدل جاتی ہیں۔

اس نظام کو تبدیل کرنا ہے تو پارٹیوں پر چھا جاؤ تاکہ جو بھی پارٹی جیتے وہ اللہ کا نظام نافذ کرے۔ اگر آپ کو اس کی پرواہ نہیں، تو میں اس سرکس میں کسی ایک کی حمایت کر کے اپنے اللہ اور اپنے رسول صلی اللہ علیہ وآلہ وسلم کے سامنے شرمندہ نہیں ہونا چاہتا۔
Copied Qaiser Ahmed Raja ❤️

16/02/2024

بائیکاٹ PSL

13/02/2024

Gradient Boosting:
Imagine you're trying to improve your skills in a sport by working on your weaknesses. You practice, get feedback, and focus on areas needing improvement. Gradient boosting does something similar with predictions. It builds a model, finds where it made errors, and then builds another model that tries to correct those errors. This process repeats, with each new model focusing more on the hard-to-predict cases. It's like having a team of coaches each focusing on improving a specific part of your performance, gradually boosting your overall skill level.It's like Reinforcement learning that act on environment gets feedback and improve by removing error . it works on the basis of trail and error. You learn to drive car first time your teacher tell instructions and you strart to drive a car you make 5 mistakes and teacher correct that error and teach again this loop is run again and again and reduce your eror.

In our live class of Ai hope to skill Sir sheraz and Sir Haris teach us whenever we have to difficulty in understanding any topic tgan Sir Irfan Malik stand up to simply with real life examples,means during Sir Haris and Sir sheraz teaching few errors left and we haven't cleared the concept so Sir Irfan clear us by removing error is also real life example of gradient descent 😁😁😁

13/02/2024

Random Forest:
Random Forest is a powerful machine learning algorithm that's used for both classification and regression tasks. It belongs to the ensemble learning family, meaning it relies on combining multiple models to improve the overall performance. The "forest" it refers to is a collection of decision trees, which are the individual models that make up the ensemble. Here's a simple way to understand how Random Forest works and why it's so effective:

Analogy:
Imagine you're trying to decide where to go on vacation and you ask several of your friends for their recommendations. Each friend evaluates your question based on their experiences and preferences (like budget, climate, activities, etc.), and gives you a destination they think you'll enjoy. In the end, you decide based on the most frequently recommended destination among your friends. This process of consulting multiple friends and aggregating their advice is similar to how Random Forest makes predictions. Another example is currently few days ago election 2024 held on 8 february. Public votes their Leader on behalf of their talent to improve the economy of pakistan etc. People give their recommendations by giving vote and elect on PM on the bases of majority vote and aggregating their advice is similar to how Random Forest makes predictions.

How Random Forest Works:
Creating the Forest:

Random Forest starts by creating multiple decision trees. Each tree is trained on a random sample of the data. This process is known as bootstrapping.
When building each tree, Random Forest also randomly selects a subset of features (like age, income, job type, etc.) for each split in the decision tree. This adds to the diversity among the trees and is key to the algorithm's success.
Making Predictions:

To make a prediction, Random Forest asks each of the decision trees in the forest to make a prediction on the input data.
For classification tasks, the final prediction is the class that gets the most votes from the trees (like choosing the most recommended vacation destination).
For regression tasks, it averages the predictions of all the trees.

13/02/2024

Decision Trees:
Take decision at every nodes.
One feature select as a root node.
The last node is called leaf node where done final decision.
Make data from impurity to purity.
Now, imagine you're trying to decide what to wear based on the weather. A decision tree is like a flowchart where you start at the top and make decisions at each branch. For example, if it's raining, you choose to wear a raincoat; if it's sunny, you might opt for a t-shirt.Itmeans it works like nested if else.In machine learning, decision trees make decisions based on data features (like weather conditions) to predict outcomes (like clothing choices). During cricket match if there is raining match will stop if there no rain match will be continue. Another example we get is if student have above 80 percent marks then student is extra ordinary, if marks is more than 60 but less than 80 Student talent is normal if below 50 student is poor.They use concepts like "Gini impurity" (a measure of how often a randomly chosen element would be incorrectly identified) and "entropy" (a measure of randomness or uncertainty) to build the most efficient tree.

13/02/2024

Logistic Regression:
Imagine you're a doctor trying to predict whether a patient has a certain disease based on their symptoms. Logistic regression is a bit like a specialized calculator that takes in various symptoms (like fever, cough) and then tells you the probability (a number between 0 and 1) of the patient having the disease.for example you want to diagnose covid-19 and there is multiple symptoms of covid max number of symptoms close to 1 means max posiblities of Covid-19. The closer the number is to 1, the more likely the patient has the disease. Logistic regression uses a special function called the "sigmoid" to do this. The sigmoid curve looks like an "S," which smoothly transitions from 0 (no chance of the disease) to 1 (certain of the disease) as the symptoms become more indicative of the disease. It means you have to make the thrisholed line for prediction between 0 and 1 e.g 0.5 if number is above 0.5 max possiblity of Covid-19 below 0.5 min possiblity of Covid-19.

Please follow below link and subscribe my YouTube channel 😁😁 fr ma YouTube videos b bnaya kron ga inshallah 🤗🙈

https://www.youtube.com/

10/02/2024

انگوٹھے کا نشان مٹ گیا لیکن رزلٹ ابھی تک نہیں آیا 🫡

09/02/2024

میں حافظ نعیم الرحمٰن کے سنگ لڑنے کیلئے تیار ہوں اور آپ؟ Trending #
حل صرف جماعت اسلامی 😍❤️✌️

09/02/2024

*Value swapping using Two variables😅😁*

06/02/2024

08/01/2024

Moye Moye 😁

16/12/2023

فیس بک پر Puzzle والی ٹرینڈ دیکھ کر میں اس نتیجے پر پہنچا ہوں کہ اکثریت لوگ اپنی شکل سے مطمئن نہیں ہے اور مارک کے بنائے ہوئے شکل کے خواہش مند ہیں۔ پہلے خوبصورت ہونے کی خواہش خواتین میں ہوتی تھی اب ماشاءاللہ ہمارے مرد بھی اس میدان میں خواتین کے شانہ بہ شانہ کھڑے ہیں۔

میری دعا ہے کہ اللہ سب کو خوبصورت اور خوب سیرت بنائے۔

03/12/2023

Artificial general intelligence (AGI)

30/11/2023

The recent chaos at artificial intelligence (AI) company OpenAI was not due to a disagreement over safety, the president of Microsoft has said.

There were fears the sacking of OpenAI boss Sam Altman followed a "dangerous" discovery at the ChatGPT creator.

Brad Smith told the BBC the shock dismissal "wasn't fundamentally about a concern like that."

Microsoft is the top investor in OpenAI and offered to hire Mr Altman before he was reinstated at the firm last week.
Source:BBC

27/11/2023

انڈیا میں:
ایلون مسک نے چیلنج دیا ہے کہ سرکار 15 فیصد سبسڈی دے تو میں دو ارب ڈالر کا Tesla پلانٹ لگا دوں گا۔

پاکستان میں:
مفتی نیفو نے مرزے جہلمی کو چیلنج دیاہے کہ ۔۔۔۔ اوئے باہر نکل۔

عزیر سالار

25/11/2023

What is Ai?
What is future going to be like?

AI, or Artificial Intelligence, refers to the development of computer systems that can perform tasks that typically require human intelligence. This includes things like learning, problem-solving, understanding natural language, and more.

As for the future, it's fascinating but also uncertain. AI is likely to play an increasingly significant role in various aspects of life, from healthcare and transportation to entertainment and communication. However, how it will precisely shape our future depends on how it's developed, regulated, and integrated into society. Many envision AI making certain tasks more efficient while also potentially creating new job opportunities. Yet, there are concerns about its impact on employment, privacy, and ethics that we'll need to navigate.

19/11/2023

Dance started in Ahmedabad 👌❤️

29/10/2023

Generative Artificial Intelligence (AI) is a type of technology that's pretty smart and creative. It's like a virtual artist or writer. Here's how it works:

Learning from Data: Generative AI learns by looking at lots of examples. For instance, if it's trained to create art, it studies tons of paintings to understand different styles.

Creating New Stuff: Once it learns, it can make new things all on its own. If it's an art AI, it can create unique paintings, even though no human told it exactly what to paint.

Variety: Generative AI can generate lots of different things, not just one. For example, it can produce different styles of music or generate various faces in a portrait.

Text Generation: It can write text, too! Some AI can write stories, poems, or even answer questions like I'm doing right now.

GPT-3: One famous example of generative AI is GPT-3. GPT-3 read lots of books, articles, and websites, so it can help answer your questions and create written content.

Challenges: But remember, generative AI isn't perfect. It can make mistakes or create weird stuff sometimes. Humans need to check its work.

In a nutshell, generative AI is a clever tool that can make new things, whether it's art, music, or words, by learning from what it's seen before. It's like having a creative robot friend!

28/10/2023

Classification and regression in very simplest way and easy to understand

28/10/2023

Classification and regression are two types of tasks in machine learning.

Classification is like sorting objects into categories. Imagine you have fruits and you want to sort them as either "apples" or "bananas." That's classification. It's like putting things in boxes with labels.

Regression, on the other hand, is about making predictions with numbers. Suppose you want to predict the price of a house based on its size. You measure the size and predict the price in dollars. That's regression. It's about finding the relationship between numbers.

In a nutshell, classification is for sorting things into groups, while regression is for making numerical predictions.

28/10/2023

جن کو امید درکار ہے ان کیلیے ۔ ❤️

Pakistan Qualification Senario For Semifinal.

Pakistan have to Win Their All Remaining 3 Matches (Against) Bangladesh New Zealand England

Option 1- if Australia lost their 2 Matches (Against) New Zealand England Afganistan Bangladesh

Option 2- If South Africa lost Their All Remaining 3 Matches (Against) New Zealand India Afghanistan

Option 3- If India Lost Their All Remaining 4 Matches (Against) England Sri Lanka South Africa Netherlands

Option 4- If New Zealand Lost Their 2 Matches (Against) Australia South Africa Sri Lanka

27/10/2023

newest course from Andrew Ng and DeepLearning.AI: Generative AI for Everyone is coming soon!

As an AI for Everyone learner, you might wonder what's different in this new course. The world of AI has changed rapidly in the past 18 months. Large language models (LLMs) and other generative AI applications have taken the world by storm, and continue to evolve. Our new course teaches the most up-to-date information regarding these revolutionary tools and technologies.

26/10/2023

Can AI grasp related concepts after learning only one?
Research shows new promise for 'compositional generalization'
Date:
October 25, 2023
Source:
New York University
Summary:
Researchers have now developed a technique that advances the ability of these tools, such as ChatGPT, to make compositional generalizations. This technique, Meta-learning for Compositionality, outperforms existing approaches and is on par with, and in some cases better than, human performance.

26/10/2023

What is Artificial intelligence:
AI, or Artificial Intelligence, is like teaching computers to think and learn like humans. It helps machines do smart things, such as recognizing images, understanding language, and making decisions.
Follow Ikramullah Naqvi. For more Information about Computer science and Artificial intelligence in very simplest way.
Sir Irfan Malik k Next badge k lectures ki simplest and explanation es page pa post keya kron ga inshallah ... Taaki sb ko saani or zeyada faida ho

26/10/2023

There are two main types:

Supervised Learning: This is like when you tell your robot friend which fruit is which. You give the computer lots of examples with labels (like "apple" or "banana"), and it learns to make predictions based on those labels.

Unsupervised Learning: In this case, you let the computer find patterns on its own. It's like your robot friend figuring out that red things are usually apples without you telling it. The computer groups things together based on similarities it finds in the data.

Machine learning helps computers do all sorts of smart things, like recognizing faces in photos, understanding what you're saying to them, and even playing games. It's like teaching them to learn from experiences, just like you learn from playing with toys and listening to stories.

26/10/2023

Machine learning ki do types:

Supervised Learning: Isme, model ko labeled data di jati hai, aur model ko sikhaya jata hai ki data ke adhar par samasya ka samadhan kaise nikala jata hai. Yani, model ko sikhaya jata hai ki input aur output ke beech ke sambandh ko samajhna aur naye data ke liye anumanit results nikalna.

Unsupervised Learning: Isme, model ko labeled data nahi di jati hai. Model ko data me chhupi patterns, samanataayein, ya clusters khud se dhundhni hoti hain. Is prakar ke machine learning me model khud se data ko samjhta hai aur usme se behtar samasya ka samadhan nikalta hai.

Yeh do mukhya machine learning prakar hain, aur inka upayog alag-alag prakar ki samasyao ka samadhan nikalne ke liye hota hai.