Machine learning books and papers pinned «با عرض سلام در مقاله زیر جهت سابمیت نیاز به نفر دوم داریم Title: FFChurn: Fusion Former for Customer Churn Classification Based on Transformer, FEDformer, and Informer Abstract: Customer churn prediction is a key issue in customer relationship management…»
🔥 8 skills = 8 free certifications >>>
AI (Microsoft) -
https://learn.microsoft.com/en-us/training/paths/get-started-artificial-intelligence/
Deep learning (NVIDIA) -
https://learn.nvidia.com/en-us/training/self-paced-courses
Data science (IBM) -
https://skillsbuild.org/students/course-catalog/data-science
Data Analyst (Microsoft) -
https://learn.microsoft.com/en-us/training/paths/data-analytics-microsoft/
Python (Microsoft) -
https://learn.microsoft.com/en-us/shows/intro-to-python-development/
SQL (Infosys) -
https://www.coursejoiner.com/freeonlinecourses/infosys-free-certification-course-9/
Java (Infosys) -
https://www.coursejoiner.com/uncategorized/infosys-launched-free-java-certification-course/
Cloud computing (AWS) -
https://explore.skillbuilder.aws/learn/course/134/aws-cloud-practitioner-essentials
@Machine_learn
AI (Microsoft) -
https://learn.microsoft.com/en-us/training/paths/get-started-artificial-intelligence/
Deep learning (NVIDIA) -
https://learn.nvidia.com/en-us/training/self-paced-courses
Data science (IBM) -
https://skillsbuild.org/students/course-catalog/data-science
Data Analyst (Microsoft) -
https://learn.microsoft.com/en-us/training/paths/data-analytics-microsoft/
Python (Microsoft) -
https://learn.microsoft.com/en-us/shows/intro-to-python-development/
SQL (Infosys) -
https://www.coursejoiner.com/freeonlinecourses/infosys-free-certification-course-9/
Java (Infosys) -
https://www.coursejoiner.com/uncategorized/infosys-launched-free-java-certification-course/
Cloud computing (AWS) -
https://explore.skillbuilder.aws/learn/course/134/aws-cloud-practitioner-essentials
@Machine_learn
NVIDIA
NVIDIA Self-Paced Training and Courses
Learn how to set up an end-to-end project in eight hours or how to apply a specific technology or development technique in two hours—anytime, anywhere.
❤2
"The Mathematics of Bitcoin" is a concise work that analyzes Bitcoin from a mathematical perspective. 📊
It utilizes probability theory, stochastic processes, martingales, combinatorics, and special functions to explore the mechanisms of the Bitcoin protocol. 🧮
In particular, the authors examine the probability of double-spending, the profitability of mining, block generation, miner strategies, and the resilience of the protocol. ⛏️
If you want to delve deeper, I also recommend "Bitcoin and Cryptocurrency Technologies" from Princeton University. This is a much broader introduction to cryptographic hash functions, digital signatures, consensus, Proof of Work, mining, transactions, anonymity, security, and the incentive system in cryptocurrencies. 🎓
The Mathematics of Bitcoin:
https://arxiv.org/pdf/2003.00001
Bitcoin and Cryptocurrency Technologies:
https://d28rh4a8wq0iu5.cloudfront.net/bitcointech/readings/princeton_bitcoin_book.pdf
@Machine_learn
It utilizes probability theory, stochastic processes, martingales, combinatorics, and special functions to explore the mechanisms of the Bitcoin protocol. 🧮
In particular, the authors examine the probability of double-spending, the profitability of mining, block generation, miner strategies, and the resilience of the protocol. ⛏️
If you want to delve deeper, I also recommend "Bitcoin and Cryptocurrency Technologies" from Princeton University. This is a much broader introduction to cryptographic hash functions, digital signatures, consensus, Proof of Work, mining, transactions, anonymity, security, and the incentive system in cryptocurrencies. 🎓
The Mathematics of Bitcoin:
https://arxiv.org/pdf/2003.00001
Bitcoin and Cryptocurrency Technologies:
https://d28rh4a8wq0iu5.cloudfront.net/bitcointech/readings/princeton_bitcoin_book.pdf
@Machine_learn
❤2
🔖 ML algorithms in visualizations
A useful repository that helps you understand how machine learning algorithms work – through interactive diagrams and step-by-step explanations.
You can run it in your browser or locally using Docker.
⛓ Link to GitHub
https://github.com/gavinkhung/machine-learning-visualized
@Machine_learn
A useful repository that helps you understand how machine learning algorithms work – through interactive diagrams and step-by-step explanations.
You can run it in your browser or locally using Docker.
⛓ Link to GitHub
https://github.com/gavinkhung/machine-learning-visualized
@Machine_learn
❤6
Matrix Calculus for Machine Learning and Beyond! — a free ebook from MIT.
This is the 2025 MIT textbook by Alan Edelman, Steven G. Johnson, and Paige Bright.
The book directly connects matrix calculus to modern machine learning.
Inside:
* Derivatives of matrices and vectors
* Jacobian and Hessian
* Matrix decompositions
* Optimization
* Differentiation in reverse mode
* Backpropagation of error
* Automatic differentiation
* Derivatives through ODEs
* Problems focused on machine learning
This is a comprehensive mathematical bridge between linear algebra, calculus, optimization, backpropagation, and machine learning.
Free ebook:
https://geni.us/Matrix-Calculus-Book
@Machine_learn
This is the 2025 MIT textbook by Alan Edelman, Steven G. Johnson, and Paige Bright.
The book directly connects matrix calculus to modern machine learning.
Inside:
* Derivatives of matrices and vectors
* Jacobian and Hessian
* Matrix decompositions
* Optimization
* Differentiation in reverse mode
* Backpropagation of error
* Automatic differentiation
* Derivatives through ODEs
* Problems focused on machine learning
This is a comprehensive mathematical bridge between linear algebra, calculus, optimization, backpropagation, and machine learning.
Free ebook:
https://geni.us/Matrix-Calculus-Book
@Machine_learn
❤5👍1
🔖Computer Science Fundamentals from MIT
We found the textbook Mathematics for Computer Science – covering the mathematics that underlies algorithms and computer science.
Logic, graphs, combinatorics, probability, induction, recurrence relations, and discrete structures – all in one place.
⛓️ Link to the textbook
https://ocw.mit.edu/courses/6-042j-mathematics-for-computer-science-spring-2015/mit6_042js15_textbook.pdf
@Machine_learn
We found the textbook Mathematics for Computer Science – covering the mathematics that underlies algorithms and computer science.
Logic, graphs, combinatorics, probability, induction, recurrence relations, and discrete structures – all in one place.
⛓️ Link to the textbook
https://ocw.mit.edu/courses/6-042j-mathematics-for-computer-science-spring-2015/mit6_042js15_textbook.pdf
@Machine_learn
❤3