Learn AI for free directly from top companies. 🚀
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
💬 Comment "Learning" if you find this helpful.
🔄 Repost so others can take help.
🔖 Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://xn--r1a.website/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
💬 Comment "Learning" if you find this helpful.
🔄 Repost so others can take help.
🔖 Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://xn--r1a.website/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.
❤13👍4
My favorite way to work with multiple filters in pandas.Series — not a chain of .loc, but a single mask. 🐼
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. 🤯
It's more reliable to gather everything into one expression:
One mask, one point of truth. ✅
It's easier to debug. Fewer surprises when the code grows. 🚀
#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. 🤯
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. ✅
It's easier to debug. Fewer surprises when the code grows. 🚀
#Pandas #Python #DataScience #CodingTips #DataEngineering #Debugging
Telegram
AI PYTHON 🌟
You’ve been invited to add the folder “AI PYTHON 🌟”, which includes 15 chats.
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Forwarded from Machine Learning
500 AI/ML/Computer Vision/NLP projects with code 🚀
This is a large collection of 500 ready-made projects in the field of machine learning, deep learning, computer vision, and NLP 🧠
All examples come with code, so you can not just read them, but immediately analyze and run them ⚙️
➡️ 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
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⭐️ 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 🧠
All examples come with code, so you can not just read them, but immediately analyze and run them ⚙️
➡️ 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
✨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
❤12