sudo certbot -i nginx -d mqbakery.com -d *.mqbakery.com -a manual
sudo nginx -t
sudo systemctl reload nginx
or
docker stop docker-webserver-1
docker start docker-webserver-1
NB- When you add acme challenge in godaddy, don't forget to remove the domain name from txt name. eg:_acmechallenge.mqbakery.com may be written as only acme_challenge
sudo apt update
sudo apt install python3
Verify Installation:
python3 --version
python3
sudo apt install python3-pip
pip3 --version
Interpreter -
Python3 filename.py
https://support.google.com/analytics/answer/9304153?hl=en
https://analytics.google.com/analytics/web/#/p213025502/reports/intelligenthome
https://www.youtube.com/watch?v=QmEOPuJr05w&list=PLI5YfMzCfRtZ4bHJJDl_IJejxMwZFiBwz&index=4
Setting up a Google Analytics account involves a few steps. Follow these step-by-step instructions:
Create a Google Account: If you don't have a Google Account, you'll need to create one. Visit the Google Account creation page and follow the instructions.
Sign in to Google Analytics: Once you have a Google Account, go to the https://analytics.google.com/analytics/web/#/ and sign in with your Google Account credentials.
Set Up a New Google Analytics Account:
Set Up a Property:
Configure Data Sharing Settings:
Create a Google Analytics 4 Property:
Agree to Terms and Create:
Install the Tracking Code:
Verify Tracking Installation:
Explore Google Analytics:
Remember that it may take some time for data to appear in your reports, so be patient. Regularly check your Google Analytics account to gain insights into your website's performance and user behavior.
Below is the Google tag for this account. Copy and paste it in the code of every page of your website, immediately after the <head> element. Don’t add more than one Google tag to each page.
There are several excellent free courses available for Artificial Intelligence (AI) studies. Here are some of the best free courses for AI:
1. Stanford University's CS229: Machine Learning: This course is available for free online and covers various machine learning algorithms and techniques. It is widely regarded as one of the best resources for learning machine learning.
2. Stanford University's CS231n: Convolutional Neural Networks for Visual Recognition: This course focuses on deep learning techniques applied to computer vision. It covers topics such as CNNs, image classification, object detection, and more.
3. University of Helsinki's Elements of AI: This online course provides a beginner-friendly introduction to AI. It covers various AI concepts and applications, offering a comprehensive overview of the field.
4. Google's Machine Learning Crash Course: This free online course offers an introduction to machine learning concepts. It covers topics such as linear regression, classification, neural networks, and more.
5. Microsoft's Artificial Intelligence (AI) Ethics, Law, and Policy: This course explores the ethical implications of AI. It covers topics such as fairness, transparency, privacy, and bias in AI systems.
6. deeplearning.ai's Deep Learning Specialization: This specialization on Coursera offers the first course, "Neural Networks and Deep Learning," for free. It provides a comprehensive introduction to deep learning techniques.
7. Berkeley's Artificial Intelligence: This course, available on edX, covers various AI topics such as search algorithms, logic, planning, and more. It provides a solid foundation in AI principles.
8. Fast.ai's Practical Deep Learning for Coders: This course is designed to make deep learning accessible for coders. It covers practical aspects of deep learning and provides hands-on experience with real-world applications.
9. UC San Diego's Machine Learning Fundamentals: This course offers an overview of machine learning principles, algorithms, and applications. It covers topics such as regression, clustering, and reinforcement learning.
10. IBM's Applied AI: This course on Coursera explores various AI applications in industries like healthcare, finance, and cybersecurity. It offers insights into how AI is being used in real-world scenarios.
These free courses provide a solid foundation in AI and cover a range of topics including machine learning, deep learning, ethics, and applications. They are a great way to get started and gain knowledge in the field of AI without incurring any cost.
