Learn AI for free directly from top companies. ๐
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
๐ฌ Comment "Learning" if you find this helpful.
๐ Repost so others can take help.
๐ Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://t.me/CodeProgrammer
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
๐ฌ Comment "Learning" if you find this helpful.
๐ Repost so others can take help.
๐ Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://t.me/CodeProgrammer
Grow with Google US
AI Training to Grow Your Career | Google
Learn all about AI & how to supercharge your work or business. We offer AI courses and tools that will help you build essential AI skills.
โค12๐4
My favorite way to work with multiple filters in pandas.Series โ not a chain of .loc, but a single mask. ๐ผ
The chain looks neat, but breaks on real data and easily gives unexpected results:
The problem is that the second .loc again looks at the original s, not the already filtered result. The logic gets messy. ๐คฏ
It's more reliable to gather everything into one expression:
One mask, one point of truth. โ
It's easier to debug. Fewer surprises when the code grows. ๐
#Pandas #Python #DataScience #CodingTips #DataEngineering #Debugging
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. ๐คฏ
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. โ
It's easier to debug. Fewer surprises when the code grows. ๐
#Pandas #Python #DataScience #CodingTips #DataEngineering #Debugging
Telegram
AI PYTHON ๐
Youโve been invited to add the folder โAI PYTHON ๐โ, which includes 15 chats.
โค6
Forwarded from Machine Learning
500 AI/ML/Computer Vision/NLP projects with code ๐
This is a large collection of 500 ready-made projects in the field of machine learning, deep learning, computer vision, and NLP ๐ง
All examples come with code, so you can not just read them, but immediately analyze and run them โ๏ธ
โก๏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
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
This is a large collection of 500 ready-made projects in the field of machine learning, deep learning, computer vision, and NLP ๐ง
All examples come with code, so you can not just read them, but immediately analyze and run them โ๏ธ
โก๏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
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค12
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)โฆ
๐ท Category: development
๐ Language: English (US)
๐ฅ Students: 38,796 students
โญ๏ธ Rating: 4.3/5.0 (964 reviews)
๐โโ๏ธ Enrollments Left: 9
โณ Expires In: 0D:4H:4M
๐ฐ Price:$9.59 โน FREE
๐ Coupon:
โ ๏ธ Watch 2 short ads to unlock your free access.
๐ By: https://t.me/Udemy26
#Programming #Coding #Development #Tech #Python #DataScience
Python Programming for Beginners: Learn Python from Scratch (Master Data Analysis, Step-by-Step with Practice Exercises)โฆ
๐ท Category: development
๐ Language: English (US)
๐ฅ Students: 38,796 students
โญ๏ธ Rating: 4.3/5.0 (964 reviews)
๐โโ๏ธ Enrollments Left: 9
โณ Expires In: 0D:4H:4M
๐ฐ Price:
๐ Coupon:
02E367A95E4BACD13ECEโ ๏ธ Watch 2 short ads to unlock your free access.
๐ By: https://t.me/Udemy26
#Programming #Coding #Development #Tech #Python #DataScience
โค2๐1
Transformers become more understandable when you can "poke" the model directly. ๐ง โจ
Transformer Explainer is an interactive visualization tool for studying how text-generating transformer-based models, such as GPT, work. ๐
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. ๐๐
Key features: ๐
- Live GPT-2 in the browser - experiment without setting up a separate model server ๐ป
- Your own text - try your own prompts and see how the model processes them โ๏ธ
- Internal components - observe the operations working inside the transformer ๐ง
- Focus on predicting the next token - link each visual step to the model's predictions ๐ฏ
- Local development - clone the repository, install dependencies, and run via npm for in-depth study โ๏ธ
It's open-source (MIT license). ๐
https://github.com/poloclub/transformer-explainer
#AI #MachineLearning #GPT #DataScience #TechTools #OpenSource
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Transformer Explainer is an interactive visualization tool for studying how text-generating transformer-based models, such as GPT, work. ๐
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. ๐๐
Key features: ๐
- Live GPT-2 in the browser - experiment without setting up a separate model server ๐ป
- Your own text - try your own prompts and see how the model processes them โ๏ธ
- Internal components - observe the operations working inside the transformer ๐ง
- Focus on predicting the next token - link each visual step to the model's predictions ๐ฏ
- Local development - clone the repository, install dependencies, and run via npm for in-depth study โ๏ธ
It's open-source (MIT license). ๐
https://github.com/poloclub/transformer-explainer
#AI #MachineLearning #GPT #DataScience #TechTools #OpenSource
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค5
Reinforcement Learning Methods and Tutorials ๐ง ๐
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 ๐
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. ๐โจ
#ReinforcementLearning #MachineLearning #AI #DeepLearning #TechTutorials #DataScience
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
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 ๐
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. ๐โจ
#ReinforcementLearning #MachineLearning #AI #DeepLearning #TechTutorials #DataScience
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค12
Top YouTube Channels to Master Tech Skills ๐
1. SQL ๐ป
๐ youtube.com/@joeyblue1
2. Excel ๐
๐ youtube.com/@excelisfun
3. Statistics ๐
๐ youtube.com/@statquest
4. Math ๐งฎ
๐ youtube.com/results?searchโฆ
5. Python ๐
๐ youtube.com/@BroCodez
6. Data Analysis ๐
๐ youtube.com/@AlexTheAnalyst
7. Machine Learning ๐ค
๐ youtube.com/@campusx-officโฆ
8. Deep Learning ๐ง
๐ youtube.com/@deeplizard
9. Java โ
๐ youtube.com/@Telusko
10. Big Data ๐ฆ
๐ youtube.com/@thedatatech
11. Data Engineering โ๏ธ
๐ youtube.com/@dataengineeriโฆ
12. NLP (Natural Language Processing) ๐ฃ๏ธ
๐ youtube.com/@codebasics
13. Computer Vision & AI ๐๏ธ
๐ youtube.com/@murtazasworksโฆ
14. Generative AI โจ
๐ youtube.com/@sunnysavita10
15. University-Level Courses ๐
๐ youtube.com/@stanfordonline
๐ youtube.com/@mitocw
16. All-in-One Learning ๐
๐ youtube.com/@freecodecamp
#TechSkills #YouTube #DataScience #Programming #MachineLearning #LearnTech
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
1. SQL ๐ป
๐ youtube.com/@joeyblue1
2. Excel ๐
๐ youtube.com/@excelisfun
3. Statistics ๐
๐ youtube.com/@statquest
4. Math ๐งฎ
๐ youtube.com/results?searchโฆ
5. Python ๐
๐ youtube.com/@BroCodez
6. Data Analysis ๐
๐ youtube.com/@AlexTheAnalyst
7. Machine Learning ๐ค
๐ youtube.com/@campusx-officโฆ
8. Deep Learning ๐ง
๐ youtube.com/@deeplizard
9. Java โ
๐ youtube.com/@Telusko
10. Big Data ๐ฆ
๐ youtube.com/@thedatatech
11. Data Engineering โ๏ธ
๐ youtube.com/@dataengineeriโฆ
12. NLP (Natural Language Processing) ๐ฃ๏ธ
๐ youtube.com/@codebasics
13. Computer Vision & AI ๐๏ธ
๐ youtube.com/@murtazasworksโฆ
14. Generative AI โจ
๐ youtube.com/@sunnysavita10
15. University-Level Courses ๐
๐ youtube.com/@stanfordonline
๐ youtube.com/@mitocw
16. All-in-One Learning ๐
๐ youtube.com/@freecodecamp
#TechSkills #YouTube #DataScience #Programming #MachineLearning #LearnTech
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค12
This media is not supported in your browser
VIEW IN TELEGRAM
๐ A useful training tool for Data Scientists ๐
๐ซก Real-world tasks from IT companies;
๐ซก SQL practice;
๐ซก Python tasks;
๐ซก Preparation for Data Science interviews.
โ Link to the training tool
https://www.stratascratch.com/
๐ท #DataScience #SQL #Python #InterviewPrep #TechTraining #DataAnalyst
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
๐ซก Real-world tasks from IT companies;
๐ซก SQL practice;
๐ซก Python tasks;
๐ซก Preparation for Data Science interviews.
โ Link to the training tool
https://www.stratascratch.com/
๐ท #DataScience #SQL #Python #InterviewPrep #TechTraining #DataAnalyst
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค6
Forwarded from Machine Learning
This media is not supported in your browser
VIEW IN TELEGRAM
A Powerful Alternative to Pandas ๐
This is an optimized replacement for Pandas that can significantly speed up data processing without requiring major changes to your code. โ๏ธ
To get started, simply replace a single import:
Performance Benchmarks demonstrate speed improvements in various use cases. ๐
More: https://colab.research.google.com/drive/1UIokuJ4cytoiVSabRDqcziDXOan8bVua?usp=sharing
#Pandas #Python #DataScience #Performance #Fireducks #BigData
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
This is an optimized replacement for Pandas that can significantly speed up data processing without requiring major changes to your code. โ๏ธ
To get started, simply replace a single import:
import fireducks.pandas as pd
Performance Benchmarks demonstrate speed improvements in various use cases. ๐
More: https://colab.research.google.com/drive/1UIokuJ4cytoiVSabRDqcziDXOan8bVua?usp=sharing
#Pandas #Python #DataScience #Performance #Fireducks #BigData
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค8๐1
A collection of resources on MLOps for those who want to understand how machine learning systems are brought to production. ๐๐ค
https://github.com/visenger/awesome-mlops
#MLOps #MachineLearning #DevOps #AI #DataScience #TechResources
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
https://github.com/visenger/awesome-mlops
#MLOps #MachineLearning #DevOps #AI #DataScience #TechResources
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค6
Forwarded from Machine Learning
๐ Over 300 real-world case studies of ML systems from top companies. ๐ค
We found a repository that collects genuine ML engineering experience โ not theory from textbooks, but real stories of implementing models in production. ๐
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. ๐๏ธ
โ Link to GitHub
https://github.com/Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies
#MachineLearning #MLCaseStudies #DataScience #Engineering #Uber #Netflix
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
We found a repository that collects genuine ML engineering experience โ not theory from textbooks, but real stories of implementing models in production. ๐
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. ๐๏ธ
โ Link to GitHub
https://github.com/Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies
#MachineLearning #MLCaseStudies #DataScience #Engineering #Uber #Netflix
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค4
Forwarded from Udemy Free Coupons
Python for Scientific Research
Master Python for Scientific Research with Practical Examplesโฆ
๐ท Category: it-and-software
๐ Language: English (US)
๐ฅ Students: 44,999 students
โญ๏ธ Rating: 4.4/5.0 (315 reviews)
๐โโ๏ธ Enrollments Left: 98
โณ Expires In: 0D:30H:30M
๐ฐ Price:$24.71 โน FREE
๐ Coupon:
โ ๏ธ Watch 2 short ads to unlock your free access.
๐ By: https://t.me/Udemy26
#Python #DataScience #Automation #FreeCourse #Udemy #OnlineLearning
Master Python for Scientific Research with Practical Examplesโฆ
๐ท Category: it-and-software
๐ Language: English (US)
๐ฅ Students: 44,999 students
โญ๏ธ Rating: 4.4/5.0 (315 reviews)
๐โโ๏ธ Enrollments Left: 98
โณ Expires In: 0D:30H:30M
๐ฐ Price:
๐ Coupon:
23182B224407CB93B374โ ๏ธ Watch 2 short ads to unlock your free access.
๐ By: https://t.me/Udemy26
#Python #DataScience #Automation #FreeCourse #Udemy #OnlineLearning
โค2