Forwarded from 🐍 Python & Raspberry 🐍
I'm_ran_Ahmad_40_Algorithms_Every_Programmer_Should_Know_Hone_your.pdf
8.8 MB
40 Algorithms Every Programmer Should Know: Hone your problem-solving skills by learning different algorithms and their implementation in Python
40 الگوریتم که هر برنامه نویس باید بداند.
پیاده سازی با پایتون
جدید 2022 ⭐️⭐️⭐️
@raspberry_python
40 الگوریتم که هر برنامه نویس باید بداند.
پیاده سازی با پایتون
جدید 2022 ⭐️⭐️⭐️
@raspberry_python
Forwarded from 🐍 Python & Raspberry 🐍 (shaghayegh)
بهترین وب سایت ها برای #دیتاساینس
اگر سایت های دیگه ای رو هم می‌شناسی حتما برامون اسمشو کامنت بزار ☺️💎
@raspberry_python
اگر سایت های دیگه ای رو هم می‌شناسی حتما برامون اسمشو کامنت بزار ☺️💎
@raspberry_python
Forwarded from آمارکده (Yegn moradi)
Python_Learn_Python_in_24_Hours.pdf
3.3 MB
📕Learning Python IN 24 Hours
کتاب آموزش پایتون در 24 ساعت؛
آموزش تصویری و روان کدنویسی پایتون
سال چاپ: 2016
🖊لاتین
اینستاگرام ما
┏━━━━━
🌐 @Amar_kadeh 📖✍️
┗━━━━━━━━━━
کتاب آموزش پایتون در 24 ساعت؛
آموزش تصویری و روان کدنویسی پایتون
سال چاپ: 2016
🖊لاتین
اینستاگرام ما
┏━━━━━
🌐 @Amar_kadeh 📖✍️
┗━━━━━━━━━━
Forwarded from DLeX: AI Python (Farzad 🦅)
MACHINE LEARNING CHEET SHEET .pdf
1.3 MB
Forwarded from 🐍 Python & Raspberry 🐍 (فرهاد ناصری زاده 🐍)
Forwarded from انجمن علمی آمار دانشگاه الزهرا(س) تهران (Zahra Esfandiar)
Wiley_Series_in_Probability_and_Statistics_Roderick_J_A_Little,.pdf
4.8 MB
(Wiley Series in Probability and Statistics) Roderick J. A. Little, Donald B. Rubin - Statistical Analysis with Missing Data, 3rd Ed.-John Wiley & Sons (2019).pdf
کتاب تحلیل داده های گمشده از دست ش ندید
دنیای داده های گمشده خیلی قشنگه 😍
@stat_alz
کتاب تحلیل داده های گمشده از دست ش ندید
دنیای داده های گمشده خیلی قشنگه 😍
@stat_alz
Forwarded from 🐍 Python & Raspberry 🐍 (Kasra :|)
intro_to_algorithms.pdf.pdf
671.1 KB
Forwarded from DLeX: AI Python (Farzad🦅)
✅ آموزش نصب تنسرفلو در ویندوز از مهندس علیرضا اخوان
#آموزش #تنسرفلو #پایتون #منابع #python
🌎 Link Review
❇️ @AI_Python
#آموزش #تنسرفلو #پایتون #منابع #python
🌎 Link Review
❇️ @AI_Python
Forwarded from آمارکده (M)
MATLAB Farsi Learning.pdf
4.5 MB
Forwarded from DLeX: AI Python (Farzad)
۲۱۵ پروژه حل شده ماشین لرنینگ در لینک زیر قابل دسترس می باشد:
https://medium.com/coders-camp/215-machine-learning-projects-solved-and-explained-7bd6fd478897
#منابع
❇️@AI_Python
https://medium.com/coders-camp/215-machine-learning-projects-solved-and-explained-7bd6fd478897
#منابع
❇️@AI_Python
Medium
215+ Machine Learning Projects Solved and Explained
215+ Machine Learning projects solved and explained using Python programming language.
Forwarded from DLeX: AI Python (Farzad🦅)
✅ کتاب الکترونیکی «تفکر آماری برای تحلیل دیتا»
Think Stats Exploratory Data Analysis in Python
«شدیدا پیشنهاد میشود که این کتاب مطالعه شود.»
#کتاب #آموزش #آمار #پایتون
🔔 GitHub code examples
🔔 Link Review
❇️ @AI_Python
Think Stats Exploratory Data Analysis in Python
«شدیدا پیشنهاد میشود که این کتاب مطالعه شود.»
#کتاب #آموزش #آمار #پایتون
🔔 GitHub code examples
🔔 Link Review
❇️ @AI_Python
Forwarded from Machine learning books and papers
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://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-unsupervised-learning.pdf
3- Deep Learning
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-deep-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- Comprehensive Stanford Master Cheat Sheet
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf
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://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf
10- Deep Learning with Keras Cheat Sheet
https://github.com/rstudio/cheatsheets/raw/master/keras.pdf
11- Visual Guide to Neural Network Infrastructures
http://www.asimovinstitute.org/wp-content/uploads/2016/09/neuralnetworks.png
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/
@Machine_learn
1- Supervised Learning
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf
2- Unsupervised Learning
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-unsupervised-learning.pdf
3- Deep Learning
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-deep-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- Comprehensive Stanford Master Cheat Sheet
https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf
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://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf
10- Deep Learning with Keras Cheat Sheet
https://github.com/rstudio/cheatsheets/raw/master/keras.pdf
11- Visual Guide to Neural Network Infrastructures
http://www.asimovinstitute.org/wp-content/uploads/2016/09/neuralnetworks.png
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/
@Machine_learn
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