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Machine Learning with Python

Machine Learning with Python

@codeprogrammer

Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.

Admin: @HusseinSheikho || @Hussein_Sheikho
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Post #3506 7.22K
To generate stunning maps from OpenStreetMap data in #Python, use Prettymaps. It enables map creation with minimal code and offers versatile customization options.

🚀 Link to Prettymaps: bit.ly/3Ps02Qj

🔖 Dive deeper into the post: bit.ly/3PxxJjm

https://t.me/CodeProgrammer ☄️
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Post #3505 6.87K
Machine Learning concepts - Intermediate Level.
Convolutional Neural Network (CNN) Layers: Convolution vs Pooling vs Fully Connected

#MachineLearning #NeuralNetwork #DeepLearning #ArtificialIntelligence #AI #Algorithms

https://t.me/CodeProgrammer 🐍
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Post #3504 6.4K
Machine Learning Algorithm basics!
Support Vector Machines (SVM) vs k-Nearest Neighbors (k-NN)

#MachineLearning #algorithms #ML #DataScience #ArtificialIntelligence #AI

https://t.me/CodeProgrammer 🐍
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Post #3492 5.43K

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Post #3488 8.65K
📊 Data Visualization Learning Roadmap

👩🏻‍💻 Many people ask me where to start to learn "data visualization"?

✏️ The truth is that data visualization has its own language that we need to learn. We need to start with the basics and then gradually move on to more complex topics.

✅ I have used some great resources along the way that I am still learning from. With every project, consultation, or course I take, my experiences grow. Here is a summary of the useful resources that have helped me:👇


1️⃣ Part One: Articles and Books:

📑 Full article by Lisa Charlotte Muth

🔗 Article link: started data visualization

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2️⃣ Books:

📚 Book: Storytelling with Data

📚 Book: Practical Charts

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3️⃣ Learning communities:

👤 Membership link: Storytelling with Data

☑️ Membership link: DataVis Community

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4️⃣ Podcasts:

🌟 Link: SWD Podcast
🌟 Link: Data Viz Today
🌟 Link: PolicyViz

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5️⃣ Key resources:

📚 Data Visualization Guide: This guide includes great resources for learning and developing data visualization skills.

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6️⃣ Training courses:

📣 Effective data visualization / Learning to turn data into art.

📣 Information design /storytelling with data in Illustrator.

📣 Data Visualization / This course provides creative tools and techniques for visualization.

➖➖➖➖➖➖➖➖➖

7️⃣ Data visualization tools:

⬅️ Link: Scimago Graphica
⬅️ Link: Datawrapper
⬅️ Link: Flourish
⬅️ Link: Tableau Public
⬅️ Link: RStudio & Python

https://t.me/CodeProgrammer ✅
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Post #3486 11K
👩‍💻 algorithms is a useful repository with a collection of algorithms implemented in Python!

🌟 It covers a wide range of algorithmic topics, including sorting, searching, graph manipulation, data structures, dynamic programming, cryptography, and more. The main goal of the repository is to provide an educational resource for learning algorithms and improving programming skills.

🔐 License: MIT

🖥 Github

https://t.me/CodeProgrammer ✅
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Post #3479 8.76K
🪙 Everything you need to get started in machine learning.

Start with Python, explore scikit-learn, and neural networks using PyTorch. Perfect for beginners—get the skills you need to advance your career in just a few hours.

Start for free ▶️ ow.ly/HBtl50UtwCA

📂 Tags: #DataScience #Python #ML #AI #LLM #Courses #Pandas #DV #GAN

http://t.me/codeprogrammer ⭐️
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Post #3478 7.89K
GANs clearly explained with visuals

This website provides a clear explanation, Try it out yourself: poloclub.github.io/ganlab/

📂 Tags: #DataScience #Python #ML #AI #LLM #Courses #Pandas #DV #GAN

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Post #3474 9.22K
15 ways to optimize neural network training

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV #MIT

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Post #3472 9.04K
👨🏻‍💻 One of the most popular GitHub repositories for "learning and using algorithms in Python" is The Algorithms - Python repo with 196K stars.

✏️ It has a lot of organized and categorized code that you can use to find, read, and run different algorithms. Everything you can think of is here; from simple algorithms like sorting to advanced algorithms for machine learning, artificial intelligence, neural networks, and more.

✅ Why should we use it?

🔢 For learning: If you're looking to learn algorithms in action, this is great.

🔢 For practice: You can take the codes, run them, and modify them to better understand.

🔢 For projects : You can even use the codes here in real-life or academic projects.

🔢 For interviews: If you're preparing for data science interviews, this is full of practical algorithms.


┌ 🏳️‍🌈 The Algorithms - Python
└ 🐱 GitHub-Repos

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV #MIT

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Post #3469 10.7K
🎥 Free course "Computational Thinking and Data Science"
📊 MIT University

👨🏻‍💻 One of the best resources I've found for learning computational thinking and data science is this free course from MIT. It covers concepts like data analysis, computational modeling, and using algorithms to solve complex problems. I've included the links to the slides and videos from the course below:👇

📄 Slides link: Lecture Slides and Files

📹 Video links: Lecture Videos

📂 Tags: #DataScience #Python #ML #AI #LLM #BIGDATA #Courses #Pandas #DV #MIT

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