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Ant AI Automated Sales Robot is an intelligent robot focused on automating lead generation and sales conversion. Its core function simulates human conversation, achieving end-to-end business conversion and easily generating revenue without requiring significant time investment.
I. Core Functions: Fully Automated "Lead Generation - Interaction - Conversion"
Precise Lead Generation and Human-like Communication: Ant AI is trained on over 20 million real social chat records, enabling it to autonomously identify target customers and build trust through natural conversation, requiring no human intervention.
High Conversion Rate Across Multiple Scenarios: Ant AI intelligently recommends high-conversion-rate products based on chat content, guiding customers to complete purchases through platforms such as iFood, Shopee, and Amazon. It also supports other transaction scenarios such as movie ticket purchases and utility bill payments.
24/7 Operation: Ant AI continuously searches for customers and recommends products. You only need to monitor progress via your mobile phone, requiring no additional management time.
II. Your Profit Guarantee: Low Risk, High Transparency, Zero Inventory Pressure, Stable Commission Sharing
We have established partnerships with platforms such as Shopee and Amazon, which directly provide abundant product sourcing. You don't need to worry about inventory or logistics. After each successful order, the company will charge the merchant a commission and share all profits with you. Earnings are predictable and withdrawals are convenient. Member data shows that each bot can generate $30 to $100 in profit per day. Commission income can be withdrawn to your account at any time, and the settlement process is transparent and open.
Low Initial Investment Risk. Bot development and testing incur significant costs. While rental fees are required, in the early stages of the project, the company prioritizes market expansion and brand awareness over short-term profits.
If you are interested, please join my Telegram group for more information and leave a message: https://news.1rj.ru/str/+lVKtdaI5vcQ1ZDA1
I. Core Functions: Fully Automated "Lead Generation - Interaction - Conversion"
Precise Lead Generation and Human-like Communication: Ant AI is trained on over 20 million real social chat records, enabling it to autonomously identify target customers and build trust through natural conversation, requiring no human intervention.
High Conversion Rate Across Multiple Scenarios: Ant AI intelligently recommends high-conversion-rate products based on chat content, guiding customers to complete purchases through platforms such as iFood, Shopee, and Amazon. It also supports other transaction scenarios such as movie ticket purchases and utility bill payments.
24/7 Operation: Ant AI continuously searches for customers and recommends products. You only need to monitor progress via your mobile phone, requiring no additional management time.
II. Your Profit Guarantee: Low Risk, High Transparency, Zero Inventory Pressure, Stable Commission Sharing
We have established partnerships with platforms such as Shopee and Amazon, which directly provide abundant product sourcing. You don't need to worry about inventory or logistics. After each successful order, the company will charge the merchant a commission and share all profits with you. Earnings are predictable and withdrawals are convenient. Member data shows that each bot can generate $30 to $100 in profit per day. Commission income can be withdrawn to your account at any time, and the settlement process is transparent and open.
Low Initial Investment Risk. Bot development and testing incur significant costs. While rental fees are required, in the early stages of the project, the company prioritizes market expansion and brand awareness over short-term profits.
If you are interested, please join my Telegram group for more information and leave a message: https://news.1rj.ru/str/+lVKtdaI5vcQ1ZDA1
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DS Interview.pdf
1.6 MB
Data Science Interview questions
#DeepLearning #AI #MachineLearning #NeuralNetworks #DataScience #DataAnalysis #LLM #InterviewQuestions
https://news.1rj.ru/str/CodeProgrammer
#DeepLearning #AI #MachineLearning #NeuralNetworks #DataScience #DataAnalysis #LLM #InterviewQuestions
https://news.1rj.ru/str/CodeProgrammer
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Do you see yourself as a programmer, researcher, or engineer?
Anonymous Poll
46%
Programmer
22%
Researcher
32%
Engineer
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by [@codeprogrammer]
---
🏛️ MIT OpenCourseWare – Machine Learning
---
#MachineLearning #LearnML #DataScience #AI
https://news.1rj.ru/str/CodeProgrammer
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Google for Developers
Machine Learning | Google for Developers
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Everyone can join his channel and make money! He gives away from $200 to $5.000 every day in his channel
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⚡️FREE ONLY FOR THE FIRST 500 SUBSCRIBERS! FURTHER ENTRY IS PAID! 👆👇
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Forwarded from ADMINOTEKA
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ML engineers, take note: structured ML reference guide
Link: https://ml-cheatsheet.readthedocs.io/en/latest/
There are no courses, no redundant theory, and no lengthy lectures here, but there are clear formulas, algorithms, the logic of ML pipelines, and a neatly structured knowledge base.
👉 @codeprogrammer
Link: https://ml-cheatsheet.readthedocs.io/en/latest/
There are no courses, no redundant theory, and no lengthy lectures here, but there are clear formulas, algorithms, the logic of ML pipelines, and a neatly structured knowledge base.
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Trackers v2.1.0 has been released. In this release, support for ByteTrack has been added - a fast tracking-by-detection algorithm that maintains stable IDs even during occlusions.
Link: https://github.com/roboflow/trackers
Trackers allows you to combine normal multi-object tracking with your detection or segmentation model.
👉 @codeprogrammer
Link: https://github.com/roboflow/trackers
pip install trackers
Trackers allows you to combine normal multi-object tracking with your detection or segmentation model.
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GitHub has launched its learning platform: all #courses and certificates in one place.
#Git, #GitHub, #MCP, using #AI, #VSCode, and much more.
And most of the content is #free: → https://learn.github.com
👉 @codeprogrammer
#Git, #GitHub, #MCP, using #AI, #VSCode, and much more.
And most of the content is #free: → https://learn.github.com
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Learn Python with the University of Helsinki
✓ With an official certificate
✓ From zero to advanced level
✓ 14 parts with practical tasks
All content is available → here
https://programming-25.mooc.fi/
👉 @codeprogrammer
✓ With an official certificate
✓ From zero to advanced level
✓ 14 parts with practical tasks
All content is available → here
https://programming-25.mooc.fi/
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Here's the full path I would recommend to build production-grade AI agents this year:
▪️ a foundation in Python and algorithms
▪️ mathematics and the basics of ML
▪️ transformers and LLMs
▪️ prompt engineering
▪️ memory and RAG
▪️ tools and integrations
▪️ frameworks like LangChain or CrewAI
▪️ multi-agent systems
▪️ testing, deployment, and security
👉 @Codeprogrammer
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SPOTO gives you free, instant access to high-quality, updated resources that help you study smarter and pass exams faster.
✅ Latest Exam Materials:
Covering #Python, #Cisco, #PMI, #Fortinet, #AWS, #Azure, #AI, #Excel, #comptia, #ITIL, #cloud & more!
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All materials are instantly downloadable
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・📝IT Exams Skill Test: https://bit.ly/3NVrgRU
・🎓Free IT courses: https://bit.ly/3M9h5su
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💬 Want exam help? Chat with an admin now!
wa.link/8fy3x4
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Want to turn any image into ASCII art? It's not magic, just simple brightness processing.
It's tedious and stupid to do it manually
img = [
[255, 0, 0],
[0, 255, 0]
]
# Now we need to pick a symbol for each pixel...
# What a hassle.Problem:
Manually selecting symbols by brightness is a pain. We need to automate the conversion of grayscale to symbols.
from PIL import Image
def image_to_ascii(path, width=100):
img = Image.open(path)
aspect = img.height / img.width
height = int(width * aspect * 0.55)
img = img.resize((width, height)).convert('L')
ascii_chars = '@%#*+=-:. '
pixels = img.getdata()
ascii_art = '\n'.join(
ascii_chars[pixel * (len(ascii_chars) - 1) // 255]
for pixel in pixels
)
lines = [ascii_art[i:i+width] for i in range(0, len(ascii_art), width)]
return '\n'.join(lines)
print(image_to_ascii('cat.jpg'))
How it works:
convert('L') converts the image to grayscale
Each pixel (0-255) is assigned a symbol from the set
The darker the pixel, the "denser" the symbol (e.g., '@'), the lighter - the "weaker" (space)
Let's write a converter with customizable palette:
class AsciiConverter:
PALETTES = {
'default': '@%#*+=-:. ',
'blocks': '█rayed ',
'detailed': '$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/\\|()1{}[]?-_+~<>i!lI;:,"^`\'. '
}
def __init__(self, palette_name='default'):
if palette_name not in self.PALETTES:
raise ValueError(f'Нет такой палитры, идиот. Выбери из: {list(self.PALETTES.keys())}')
self.chars = self.PALETTES[palette_name]
def convert(self, image_path, width=80):
# ... code to convert using self.chars ...
return ascii_result
Try specifying a non-existent palette - you'll get a clear error.
Key parameters:
🔵 Width - determines the size of the final ASCII art🔵 Character palette - affects the detail and style🔵 Aspect ratio - important for correct display🔵 Inversion - you can invert the brightness for a dark background
Important:
ASCII art isn't just a fun thing. It's used to visualize data in the console, create creative logs, and even "hide" information in plain sight.
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Numpy_Cheat_Sheet.pdf
4.8 MB
NumPy Cheat Sheet: Data Analysis in Python
This #Python cheat sheet is a quick reference for #NumPy beginners.
Learn more:
https://www.datacamp.com/cheat-sheet/numpy-cheat-sheet-data-analysis-in-python
https://news.1rj.ru/str/DataAnalyticsX
This #Python cheat sheet is a quick reference for #NumPy beginners.
Learn more:
https://www.datacamp.com/cheat-sheet/numpy-cheat-sheet-data-analysis-in-python
https://news.1rj.ru/str/DataAnalyticsX
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nature papers: 1200$
Q1 and Q2 papers 700$
Q3 and Q4 papers 400$
Doctoral thesis (complete) 600$
M.S thesis 300$
paper simulation 200$
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Q1 and Q2 papers 700$
Q3 and Q4 papers 400$
Doctoral thesis (complete) 600$
M.S thesis 300$
paper simulation 200$
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To: ██████ █████
From: Jeffrey Epstein <jeevacation@gmail.com>
25 May, 3:04 a.m.
Ты спрашивал, как я находил нужных людей. Забудь про мои вечеринки. Настоящий остров свободы — это Adminoteka.
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Хочешь знать, как попасть на этот остров? Переходи в🅰 ️ Adminoteka. Скажи, что ты от меня.
From: Jeffrey Epstein <jeevacation@gmail.com>
25 May, 3:04 a.m.
Ты спрашивал, как я находил нужных людей. Забудь про мои вечеринки. Настоящий остров свободы — это Adminoteka.
Никаких залетных каналов, только нишевые ребята с лучшей живой аудиторией.
Хочешь знать, как попасть на этот остров? Переходи в
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