Machine Learning with Python
68.1K subscribers
1.51K photos
130 videos
197 files
1.24K links
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.

Admin: @HusseinSheikho || @Hussein_Sheikho
Download Telegram
Learn AI for free directly from top companies. ๐Ÿš€

1 - Anthropic:
anthropic.skilljar.com

2 - Google:
grow.google/ai

3 - Meta:
ai.meta.com/resources/

4 - NVIDIA:
developer.nvidia.com/cuda

5 - Microsoft:
learn.microsoft.com/en-us/training/

6 - OpenAI:
academy.openai.com

7 - IBM:
skillsbuild.org

8 - AWS:
skillbuilder.aws

9 - DeepLearning.AI:
deeplearning.ai

10 - Hugging Face:
huggingface.co/learn

๐Ÿ’ฌ Comment "Learning" if you find this helpful.

๐Ÿ”„ Repost so others can take help.

๐Ÿ”– Must bookmark for future reference.

#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://t.me/CodeProgrammer
โค12๐Ÿ‘4
My favorite way to work with multiple filters in pandas.Series โ€” not a chain of .loc, but a single mask. ๐Ÿผ

The chain looks neat, but breaks on real data and easily gives unexpected results:

s = pd.Series([10, 15, 20, 25, 30])
s.loc[s > 20].loc[s % 2 == 1]

The problem is that the second .loc again looks at the original s, not the already filtered result. The logic gets messy. ๐Ÿคฏ

It's more reliable to gather everything into one expression:

s = pd.Series([10, 15, 20, 25, 30])

mask = (s > 20) & (s % 2 == 1)
result = s.loc[mask]

One mask, one point of truth. โœ…

It's easier to debug. Fewer surprises when the code grows. ๐Ÿš€

#Pandas #Python #DataScience #CodingTips #DataEngineering #Debugging
โค6
Forwarded from Machine Learning
500 AI/ML/Computer Vision/NLP projects with code ๐Ÿš€

This is a large collection of 500 ready-made projects in the field of machine learning, deep learning, computer vision, and NLP ๐Ÿง 

All examples come with code, so you can not just read them, but immediately analyze and run them โš™๏ธ

โžก๏ธ Link to GitHub:
https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

#AI #MachineLearning #DeepLearning #ComputerVision #NLP #DataScience

โœจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk

โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค12
Forwarded from Udemy Free Coupons
Python Programming for Beginners: Learn Python from Scratch

Python Programming for Beginners: Learn Python from Scratch (Master Data Analysis, Step-by-Step with Practice Exercises)โ€ฆ

๐Ÿท Category: development
๐ŸŒ Language: English (US)
๐Ÿ‘ฅ Students: 38,796 students
โญ๏ธ Rating: 4.3/5.0 (964 reviews)
๐Ÿƒโ€โ™‚๏ธ Enrollments Left: 9
โณ Expires In: 0D:4H:4M
๐Ÿ’ฐ Price: $9.59 โŸน FREE
๐Ÿ†” Coupon: 02E367A95E4BACD13ECE

โš ๏ธ Watch 2 short ads to unlock your free access.

๐Ÿ’Ž By: https://t.me/Udemy26
#Programming #Coding #Development #Tech #Python #DataScience
โค2๐Ÿ‘1
Transformers become more understandable when you can "poke" the model directly. ๐Ÿง โœจ

Transformer Explainer is an interactive visualization tool for studying how text-generating transformer-based models, such as GPT, work. ๐Ÿ”

It helps connect the architecture with real behavior by running a live GPT-2 directly in the browser, allowing you to enter your own text and showing how the internal components work together to predict the next tokens. ๐Ÿ”„๐Ÿ“

Key features: ๐ŸŒŸ

- Live GPT-2 in the browser - experiment without setting up a separate model server ๐Ÿ’ป
- Your own text - try your own prompts and see how the model processes them โœ๏ธ
- Internal components - observe the operations working inside the transformer ๐Ÿ”ง
- Focus on predicting the next token - link each visual step to the model's predictions ๐ŸŽฏ
- Local development - clone the repository, install dependencies, and run via npm for in-depth study โš™๏ธ

It's open-source (MIT license). ๐Ÿ“œ

https://github.com/poloclub/transformer-explainer

#AI #MachineLearning #GPT #DataScience #TechTools #OpenSource

โœจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk

โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค5
Reinforcement Learning Methods and Tutorials ๐Ÿง ๐Ÿ“š

In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years.

Learning Resources: https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow ๐Ÿš€

Here's a collection of simple materials on methods and practical guides, covering both basic reinforcement learning algorithms and modern, recently developed, and updated advanced algorithms. ๐Ÿ“–โœจ

#ReinforcementLearning #MachineLearning #AI #DeepLearning #TechTutorials #DataScience

โœจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk

โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค12
Top YouTube Channels to Master Tech Skills ๐Ÿš€

1. SQL ๐Ÿ’ป
๐Ÿ‘‰ youtube.com/@joeyblue1

2. Excel ๐Ÿ“Š
๐Ÿ‘‰ youtube.com/@excelisfun

3. Statistics ๐Ÿ“ˆ
๐Ÿ‘‰ youtube.com/@statquest

4. Math ๐Ÿงฎ
๐Ÿ‘‰ youtube.com/results?searchโ€ฆ

5. Python ๐Ÿ
๐Ÿ‘‰ youtube.com/@BroCodez

6. Data Analysis ๐Ÿ”
๐Ÿ‘‰ youtube.com/@AlexTheAnalyst

7. Machine Learning ๐Ÿค–
๐Ÿ‘‰ youtube.com/@campusx-officโ€ฆ

8. Deep Learning ๐Ÿง 
๐Ÿ‘‰ youtube.com/@deeplizard

9. Java โ˜•
๐Ÿ‘‰ youtube.com/@Telusko

10. Big Data ๐Ÿ“ฆ
๐Ÿ‘‰ youtube.com/@thedatatech

11. Data Engineering โš™๏ธ
๐Ÿ‘‰ youtube.com/@dataengineeriโ€ฆ

12. NLP (Natural Language Processing) ๐Ÿ—ฃ๏ธ
๐Ÿ‘‰ youtube.com/@codebasics

13. Computer Vision & AI ๐Ÿ‘๏ธ
๐Ÿ‘‰ youtube.com/@murtazasworksโ€ฆ

14. Generative AI โœจ
๐Ÿ‘‰ youtube.com/@sunnysavita10

15. University-Level Courses ๐ŸŽ“
๐Ÿ‘‰ youtube.com/@stanfordonline
๐Ÿ‘‰ youtube.com/@mitocw

16. All-in-One Learning ๐Ÿ“š
๐Ÿ‘‰ youtube.com/@freecodecamp

#TechSkills #YouTube #DataScience #Programming #MachineLearning #LearnTech

โœจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk

โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค12
This media is not supported in your browser
VIEW IN TELEGRAM
๐Ÿ”– A useful training tool for Data Scientists ๐Ÿ“Š

๐Ÿซก Real-world tasks from IT companies;
๐Ÿซก SQL practice;
๐Ÿซก Python tasks;
๐Ÿซก Preparation for Data Science interviews.

โ›“ Link to the training tool
https://www.stratascratch.com/

๐Ÿท #DataScience #SQL #Python #InterviewPrep #TechTraining #DataAnalyst

โœจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk

โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค6
Forwarded from Machine Learning
This media is not supported in your browser
VIEW IN TELEGRAM
A Powerful Alternative to Pandas ๐Ÿš€

This is an optimized replacement for Pandas that can significantly speed up data processing without requiring major changes to your code. โš™๏ธ

To get started, simply replace a single import:

import fireducks.pandas as pd

Performance Benchmarks demonstrate speed improvements in various use cases. ๐Ÿ“ˆ

More: https://colab.research.google.com/drive/1UIokuJ4cytoiVSabRDqcziDXOan8bVua?usp=sharing

#Pandas #Python #DataScience #Performance #Fireducks #BigData

โœจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk

โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค8๐Ÿ‘1
A collection of resources on MLOps for those who want to understand how machine learning systems are brought to production. ๐Ÿš€๐Ÿค–

https://github.com/visenger/awesome-mlops

#MLOps #MachineLearning #DevOps #AI #DataScience #TechResources

โœจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk

โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค6
Forwarded from Machine Learning
๐Ÿ”– Over 300 real-world case studies of ML systems from top companies. ๐Ÿค–

We found a repository that collects genuine ML engineering experience โ€“ not theory from textbooks, but real stories of implementing models in production. ๐Ÿ“š

Inside, you'll find case studies from Uber, Netflix, Google, and other companies: how they built the architecture, what problems arose, where the systems failed, and what solutions helped them recover. ๐Ÿ—๏ธ

โ›“ Link to GitHub
https://github.com/Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies

#MachineLearning #MLCaseStudies #DataScience #Engineering #Uber #Netflix

โœจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk

โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค4
Forwarded from Udemy Free Coupons
Python for Scientific Research

Master Python for Scientific Research with Practical Examplesโ€ฆ

๐Ÿท Category: it-and-software
๐ŸŒ Language: English (US)
๐Ÿ‘ฅ Students: 44,999 students
โญ๏ธ Rating: 4.4/5.0 (315 reviews)
๐Ÿƒโ€โ™‚๏ธ Enrollments Left: 98
โณ Expires In: 0D:30H:30M
๐Ÿ’ฐ Price: $24.71 โŸน FREE
๐Ÿ†” Coupon: 23182B224407CB93B374

โš ๏ธ Watch 2 short ads to unlock your free access.

๐Ÿ’Ž By: https://t.me/Udemy26
#Python #DataScience #Automation #FreeCourse #Udemy #OnlineLearning
โค2