Forwarded from Machine Learning Resources TP
----------------------------------------------------
AI vs ML vs DS 🤖
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Artificial Intelligence (AI) 💡
AI stands for Artificial Intelligence, which refers to the idea of imbuing machines with knowledge or intelligence. This concept has been around for about 100 years, focusing on how we can make machines think like humans.
Intelligence and AI 🤔
Intelligence is complex and involves various elements like pattern recognition, creativity, imagination, and emotional intelligence. However, the current pursuit of AI is primarily a subset of true intelligence.
Machine Learning (ML) 📊
Machine Learning (ML) is a method where we don't write explicit rules or code for every condition. Instead, we use data that has both input and output.
Deep Learning 🧠
Deep Learning is a type of machine learning that uses algorithms inspired by the way human brain neurons work.
> Key Differences 🤔
- Machine Learning: Provides data with specific features to classify items.
- Deep Learning: Automatically detects and generates features from raw data.
Why Deep Learning? 📈
Deep learning improves classification and output efficiency by adding multiple layers of neurons. The more data we provide, the better the model's performance becomes.
Machine Learning vs Deep Learning 🤔
- Machine Learning: Works best with smaller datasets.
- Deep Learning: Works best with large datasets.
About 90% of data is considered small data, which is why machine learning is still a viable option. However, deep learning excels with large datasets, making it a powerful tool for complex problems.
Neural Networks and Deep Learning : https://t.me/MachineLearningResourcesTP/3
AI vs ML vs DS 🤖
-----------------------------------------------------
Artificial Intelligence (AI) 💡
AI stands for Artificial Intelligence, which refers to the idea of imbuing machines with knowledge or intelligence. This concept has been around for about 100 years, focusing on how we can make machines think like humans.
Intelligence and AI 🤔
Intelligence is complex and involves various elements like pattern recognition, creativity, imagination, and emotional intelligence. However, the current pursuit of AI is primarily a subset of true intelligence.
Machine Learning (ML) 📊
Machine Learning (ML) is a method where we don't write explicit rules or code for every condition. Instead, we use data that has both input and output.
Deep Learning 🧠
Deep Learning is a type of machine learning that uses algorithms inspired by the way human brain neurons work.
> Key Differences 🤔
- Machine Learning: Provides data with specific features to classify items.
- Deep Learning: Automatically detects and generates features from raw data.
Why Deep Learning? 📈
Deep learning improves classification and output efficiency by adding multiple layers of neurons. The more data we provide, the better the model's performance becomes.
Machine Learning vs Deep Learning 🤔
- Machine Learning: Works best with smaller datasets.
- Deep Learning: Works best with large datasets.
About 90% of data is considered small data, which is why machine learning is still a viable option. However, deep learning excels with large datasets, making it a powerful tool for complex problems.
Neural Networks and Deep Learning : https://t.me/MachineLearningResourcesTP/3
Forwarded from Machine Learning Resources TP
An important collection of the 15 best machine learning cheat sheets.
1- Supervised Learning
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf
2- Unsupervised Learning
https://t.me/MachineLearningResourcesTP/6
3- Comprehensive Stanford Master Cheat Sheet
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf
4- Machine Learning Tips and Tricks
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-machine-learning-tips-and-tricks.pdf
5- Probabilities and Statistics
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-probabilities-statistics.pdf
6- Deep Learning
https://t.me/MachineLearningResourcesTP/5
7- Linear Algebra and Calculus
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf
8- Data Science Cheat Sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf
9- Keras Cheat Sheet
https://t.me/MachineLearningResourcesTP/7
10- Deep Learning with Keras Cheat Sheet
https://github.com/rstudio/cheatsheets/raw/master/keras.pdf
11- Visual Guide to Neural Network Infrastructures
https://t.me/MachineLearningResourcesTP/8
12- Skicit-Learn Python Cheat Sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf
13- Scikit-learn Cheat Sheet: Choosing the Right Estimator
https://scikit-learn.org/stable/tutorial/machine_learning_map/
14- Tensorflow Cheat Sheet
https://github.com/kailashahirwar/cheatsheets-ai/blob/master/PDFs/Tensorflow.pdf
15- Machine Learning Test Cheat Sheet
https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/
Neural Networks & Deep Learning
https://t.me/MachineLearningResourcesTP/3
More Machine Learning Resources Here: https://t.me/MachineLearningResourcesTP
WhatsApp Channel: https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
ENJOY LEARNING 👍👍
1- Supervised Learning
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf
2- Unsupervised Learning
https://t.me/MachineLearningResourcesTP/6
3- Comprehensive Stanford Master Cheat Sheet
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf
4- Machine Learning Tips and Tricks
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-machine-learning-tips-and-tricks.pdf
5- Probabilities and Statistics
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-probabilities-statistics.pdf
6- Deep Learning
https://t.me/MachineLearningResourcesTP/5
7- Linear Algebra and Calculus
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf
8- Data Science Cheat Sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf
9- Keras Cheat Sheet
https://t.me/MachineLearningResourcesTP/7
10- Deep Learning with Keras Cheat Sheet
https://github.com/rstudio/cheatsheets/raw/master/keras.pdf
11- Visual Guide to Neural Network Infrastructures
https://t.me/MachineLearningResourcesTP/8
12- Skicit-Learn Python Cheat Sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf
13- Scikit-learn Cheat Sheet: Choosing the Right Estimator
https://scikit-learn.org/stable/tutorial/machine_learning_map/
14- Tensorflow Cheat Sheet
https://github.com/kailashahirwar/cheatsheets-ai/blob/master/PDFs/Tensorflow.pdf
15- Machine Learning Test Cheat Sheet
https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/
Neural Networks & Deep Learning
https://t.me/MachineLearningResourcesTP/3
More Machine Learning Resources Here: https://t.me/MachineLearningResourcesTP
WhatsApp Channel: https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
ENJOY LEARNING 👍👍
GitHub
stanford-cs-229-machine-learning/en/cheatsheet-supervised-learning.pdf at master · afshinea/stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning - afshinea/stanford-cs-229-machine-learning
First try = Usually fails
First job = Usually sucks
First post = Usually flops
First message = Usually ignored
First interview = Usually no offer
Don't worry about your first. Just make an attempt, no matter how bad it is. Then you can get better.
First job = Usually sucks
First post = Usually flops
First message = Usually ignored
First interview = Usually no offer
Don't worry about your first. Just make an attempt, no matter how bad it is. Then you can get better.
To make 2025 your best year yet, focus on eliminating distractions, taking action on your goals, improving continuously, and committing to perseverance. Here are some key strategies to help you achieve success:
Eliminate Distractions
Removing negative influences and minimizing distractions is crucial for maintaining focus on your goals. Consider these tips:
- Turn unnecessary off notifications on your devices
- Create a comfortable and distraction-free work environment
- Practice meditation to improve concentration
- Use visual reminders to stay on task
Take Action on Your Goals
Don't wait for the perfect moment to start working towards your aspirations. Begin today by following these steps:
- Write down your goals and read them daily
- Break larger goals into smaller, manageable tasks
- Schedule time on your calendar for goal-related activities
- Get up early to work on your priorities
Commit to Continuous Improvement
Focus on getting better each day through small, consistent efforts[6]:
- Implement incremental changes in your daily routines
- Conduct regular performance reviews
- Encourage brainstorming and idea-sharing
- Simplify processes to increase efficiency
Persevere Through Challenges
Success requires dedication and resilience. Keep these points in mind:
- Embrace failure as a learning opportunity
- Develop a success-oriented mindset
- Share your goals with others for accountability
- Reward yourself for achieving milestones
Invest in Yourself
Prioritize education and skill development to enhance your long-term success:
- Set aside time for learning new skills
- Attend workshops or online courses
- Read books related to your field or interests
- Seek mentorship opportunities
Key Insights for Success
1. Focus is crucial: Concentrate on what truly matters and eliminate distractions to make significant progress.
2. Action beats perfection: Start working towards your goals immediately rather than waiting for the perfect moment.
3. Embrace growth: Commit to continuous learning and improvement to compound your success over time.
4. Learn from setbacks: View failures as valuable lessons that contribute to your overall journey.
5. Invest wisely: Prioritize education and skill acquisition over material possessions for long-term benefits.
6. Build good habits: Success is a product of dedication and consistent effort.
7. Act with urgency: Remember that time is precious, and the best moment to act is now.
By implementing these strategies and keeping these insights in mind, you'll be well-equipped to make 2025 your most successful and fulfilling year yet. Remember, the key is to start today and maintain your commitment to growth and improvement throughout the year.
Follow this Channel for more Tech Tips, Resources, Updates, Insights...
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Eliminate Distractions
Removing negative influences and minimizing distractions is crucial for maintaining focus on your goals. Consider these tips:
- Turn unnecessary off notifications on your devices
- Create a comfortable and distraction-free work environment
- Practice meditation to improve concentration
- Use visual reminders to stay on task
Take Action on Your Goals
Don't wait for the perfect moment to start working towards your aspirations. Begin today by following these steps:
- Write down your goals and read them daily
- Break larger goals into smaller, manageable tasks
- Schedule time on your calendar for goal-related activities
- Get up early to work on your priorities
Commit to Continuous Improvement
Focus on getting better each day through small, consistent efforts[6]:
- Implement incremental changes in your daily routines
- Conduct regular performance reviews
- Encourage brainstorming and idea-sharing
- Simplify processes to increase efficiency
Persevere Through Challenges
Success requires dedication and resilience. Keep these points in mind:
- Embrace failure as a learning opportunity
- Develop a success-oriented mindset
- Share your goals with others for accountability
- Reward yourself for achieving milestones
Invest in Yourself
Prioritize education and skill development to enhance your long-term success:
- Set aside time for learning new skills
- Attend workshops or online courses
- Read books related to your field or interests
- Seek mentorship opportunities
Key Insights for Success
1. Focus is crucial: Concentrate on what truly matters and eliminate distractions to make significant progress.
2. Action beats perfection: Start working towards your goals immediately rather than waiting for the perfect moment.
3. Embrace growth: Commit to continuous learning and improvement to compound your success over time.
4. Learn from setbacks: View failures as valuable lessons that contribute to your overall journey.
5. Invest wisely: Prioritize education and skill acquisition over material possessions for long-term benefits.
6. Build good habits: Success is a product of dedication and consistent effort.
7. Act with urgency: Remember that time is precious, and the best moment to act is now.
By implementing these strategies and keeping these insights in mind, you'll be well-equipped to make 2025 your most successful and fulfilling year yet. Remember, the key is to start today and maintain your commitment to growth and improvement throughout the year.
Follow this Channel for more Tech Tips, Resources, Updates, Insights...
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
👍1
While certificates have their own place to prove your skills, completing a course just for the sake of certificate is not going to help you at all. So whatever courses you take up, please make sure that you learn, practice and acquire that skill.
In every family tree, there is 1 person who breaks out the middle-class chain and works hard to become a millionaire and changes the lives of everyone forever.
May that be you in 2025.
May that be you in 2025.
In 1994, people told me programming was for nerds and that I should become a doctor or a lawyer instead.
10 years later, they told me that someone from India would take my job for $5/hour.
Then, no code was going to doom my career.
In 2021, Codex, then Copilot, then ChatGPT, then Devin, then OpenAI o1...
People keep yelling that "Programming is Dead," and yet the demand for good Software Engineers has never been higher.
Stop listening to midwit people. Learn to build good software, and you'll be okay. (Credits: unknown)
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
10 years later, they told me that someone from India would take my job for $5/hour.
Then, no code was going to doom my career.
In 2021, Codex, then Copilot, then ChatGPT, then Devin, then OpenAI o1...
People keep yelling that "Programming is Dead," and yet the demand for good Software Engineers has never been higher.
Stop listening to midwit people. Learn to build good software, and you'll be okay. (Credits: unknown)
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Forwarded from Java Resources TP
🔐 Top 10 Features That Make Java Secure 🔐
Java is renowned for its robust security, thanks to these features:
👉 1. JVM (Java Virtual Machine):
Isolates the code execution environment, protecting the host system from malicious code.
👉 2. Security APIs:
Built-in libraries for encryption, authentication, and secure communication (e.g., Java Cryptography Architecture).
👉 3. Security Manager:
Controls application actions at runtime, like file and network access.
👉 4. Void of Pointers:
Eliminates direct access to memory, reducing vulnerability to memory corruption.
👉 5. Memory Management:
Automated garbage collection prevents memory leaks and other misuse.
👉 6. Compile-Time Checking:
Catches errors early, ensuring code integrity before execution.
👉 7. Cryptographic Security:
Advanced encryption and secure data transmission with tools like SSL and digital signatures.
👉 8. Java Sandbox:
Isolates code execution, restricting access to critical system resources.
👉 9. Exception Handling:
Helps prevent unexpected crashes by managing runtime errors effectively.
👉 10. Java Class Loader:
Dynamically loads classes securely, preventing unauthorized code execution.
💡 These features make Java a trusted choice for secure and reliable application development.
More Tips & Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
Java is renowned for its robust security, thanks to these features:
👉 1. JVM (Java Virtual Machine):
Isolates the code execution environment, protecting the host system from malicious code.
👉 2. Security APIs:
Built-in libraries for encryption, authentication, and secure communication (e.g., Java Cryptography Architecture).
👉 3. Security Manager:
Controls application actions at runtime, like file and network access.
👉 4. Void of Pointers:
Eliminates direct access to memory, reducing vulnerability to memory corruption.
👉 5. Memory Management:
Automated garbage collection prevents memory leaks and other misuse.
👉 6. Compile-Time Checking:
Catches errors early, ensuring code integrity before execution.
👉 7. Cryptographic Security:
Advanced encryption and secure data transmission with tools like SSL and digital signatures.
👉 8. Java Sandbox:
Isolates code execution, restricting access to critical system resources.
👉 9. Exception Handling:
Helps prevent unexpected crashes by managing runtime errors effectively.
👉 10. Java Class Loader:
Dynamically loads classes securely, preventing unauthorized code execution.
💡 These features make Java a trusted choice for secure and reliable application development.
More Tips & Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
👍1
Forwarded from Python Resources TP
Official Python Docs
https://docs.python.org/3/
Tools:
http://docs.python-guide.org/en/latest/dev/virtualenvs/
http://www.pythonforbeginners.com/basics/python-pip-usage
Practice:
http://www.practicepython.org/
https://www.hackerrank.com
https://wiki.python.org/moin/PythonDecorators
Python GUI FAQ
https://docs.python.org/3/faq/gui.html
Python Resources Telegram Channel
https://t.me/PythoResourcesTP
WhatsApp Channel
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
https://docs.python.org/3/
Tools:
http://docs.python-guide.org/en/latest/dev/virtualenvs/
http://www.pythonforbeginners.com/basics/python-pip-usage
Practice:
http://www.practicepython.org/
https://www.hackerrank.com
https://wiki.python.org/moin/PythonDecorators
Python GUI FAQ
https://docs.python.org/3/faq/gui.html
Python Resources Telegram Channel
https://t.me/PythoResourcesTP
WhatsApp Channel
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
docs.python-guide.org
Pipenv & Virtual Environments — The Hitchhiker's Guide to Python
Shoutout to all the late-night coders—may your coffee be strong and your bugs be few! 🤗
There's no grading system in interview, Interviewers judges you relative to other candidates on that same question by the same interviewer.
It's a relative comparison.
It's a relative comparison.
12-Week Power Plan: Master Programming, DSA, and Build Projects for Career Success
⭕️ 1-2 Weeks:
Basics of Programming
* Choose a programming Language: Java/Cpp
* Learn about the concepts of OOPs from
Geeksforgeeks
* Practice basic programming from
Geeksforgeeks
* Practice basic Algorithms for Searching, Sorting & Recursion
* Practice basic questions of Strings and Numbers on Leetcode.
* Keep practicing the easy level questions until the basics are clear.
⭕️ 3-4 Weeks:
Complexities & Basic DSA
* Learn about Time and Space complexities
* Start with DSA from YouTube
Abdul Bari / Strivers A2Z DSA Playlist
* Only practice the basic data structures-
Arrays, Stacks, Queues, Linked Lists
* Practice Easy level questions on Leetcode
* Do this until you’re Confident
⭕️ 5-6 Week
Practicing the basics
* Solve Medium Level Leetcode questions for the topics you've prepared.
* This week aims to solidifying your basic DSA concepts.
* Give contests on Hackerrank to gain speed and getting prepared for Interviews.
⭕️ 7-10 Weeks:
Web Development / Machine Learning
* Start with Web Development or Machine Learning or any domain which will help you in building Projects.
* Complete playlists or any other courses available on it from Youtube or similar.
* Learn by building Projects. This will help you add it to your Resume as well.
* Simultaneously start with the medium level problems of the topics you’ve covered in DSA.
⭕️ 11-12 Weeks:
Advanced DSA
* Start with advanced DS like Trees & Graph
* Practice Easy & Medium level questions on these topics on Leetcode
* Learn more algorithms like Backtracking, Sliding Window, Two pointers and more
* Practice as much as you can.
Best Programming Resources: https://t.me/TechPsyche
⭕️ 1-2 Weeks:
Basics of Programming
* Choose a programming Language: Java/Cpp
* Learn about the concepts of OOPs from
Geeksforgeeks
* Practice basic programming from
Geeksforgeeks
* Practice basic Algorithms for Searching, Sorting & Recursion
* Practice basic questions of Strings and Numbers on Leetcode.
* Keep practicing the easy level questions until the basics are clear.
⭕️ 3-4 Weeks:
Complexities & Basic DSA
* Learn about Time and Space complexities
* Start with DSA from YouTube
Abdul Bari / Strivers A2Z DSA Playlist
* Only practice the basic data structures-
Arrays, Stacks, Queues, Linked Lists
* Practice Easy level questions on Leetcode
* Do this until you’re Confident
⭕️ 5-6 Week
Practicing the basics
* Solve Medium Level Leetcode questions for the topics you've prepared.
* This week aims to solidifying your basic DSA concepts.
* Give contests on Hackerrank to gain speed and getting prepared for Interviews.
⭕️ 7-10 Weeks:
Web Development / Machine Learning
* Start with Web Development or Machine Learning or any domain which will help you in building Projects.
* Complete playlists or any other courses available on it from Youtube or similar.
* Learn by building Projects. This will help you add it to your Resume as well.
* Simultaneously start with the medium level problems of the topics you’ve covered in DSA.
⭕️ 11-12 Weeks:
Advanced DSA
* Start with advanced DS like Trees & Graph
* Practice Easy & Medium level questions on these topics on Leetcode
* Learn more algorithms like Backtracking, Sliding Window, Two pointers and more
* Practice as much as you can.
Best Programming Resources: https://t.me/TechPsyche
Coding is kinda like exercising.💻 It's hard to get started, and it takes a while to see progress. You'll see many people who are more advanced than you. But the longer you do it, the better you'll get 💪 💪