Cyber Security Search Engines

It doesn’t matter how small your business or product is — what truly matters is that you’ve started. Every big achievement begins with a first step, and along the way, you’ll grow, learn, and evolve. Starting is the most important part of the journey.

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⚠️Do not try this at home🥴

𝟲 𝗜𝗕𝗠 𝗙𝗥𝗘𝗘 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 🚀💻

- AI Prompt Engineering
- Python for Data Science
- SQL Relational Database
- Data Science Fundamentals
- Introduction to Cloud
- Machine Learning with Python
 
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🎉 Jetpack Navigation 3 - navigation for Compose, written from scratch!

Let's be honest, Jetpack Navigation for Compose was no solution before it had type-safe navigation, but even then there were many questions. Google decided it was time to write a real navigation for Compose. Meet Jetpack Nav 3

Key:
👉 The developer has full control of the back stack
👉 Simpler Integration with Compose
👉 The ability to expand and implement your own navigation on basic components
👉 Animations out of the box
👉 Predictive Back support
👉 Support for adaptive layout
👉 Saving the state of each element of the back stack, including ViewModel
👉 Support for multi-modularity

So far, only the first alpha has been presented and the library still has a way to go, at least to acquire KMP support

🔗 More details in the documentation
https://developer.android.com/guide/navigation/navigation-3

🐱 Examples of use on GitHub
https://github.com/android/nav3-recipes

More Android Updates Here👇
https://t.me/mobiledevresourcestp

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60 AI tools to finish hours of work in minutes:

1. Productivity
- AI Research Assistant: otio.ai
- DeepSeek
- HeyGen
- BetterPic

2. Coding
- Replit
- Cursor
- Claude
- o3-mini-high

3. Social Media Management
- Tapilo
- Typefully
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- Postwise
- Grok

4. Text-to-Image
- Grok
- Flux
- Midjourney
- Microsoft Copilot

5. Copywriting
- Copy AI
- Writesonic
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6. Website
- Dora
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7. Meeting
- Tldv
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- Noty AI
- Fireflies

8. Resume
- Kickresume
- Resume AI
- Resume Checker
- Careerflow

9. Image to video
- Veo 2
- Kling AI
- Luma dream machine
- Sora

10. Writing
- Jasper
- HIX AI
- Textblaze
- Quillbot
- Grammarly

11. Prompt
- Snack Prompt
- CustomGPT
- PromptBox
- SiteGPT

12. UI/UX
- Figma
- Uizard
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- Photoshop

13. Design
- Canva
- Flair AI
- Designify
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14. Logo Generator
- Namelix
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- Lovo AI
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Elon Musk's xAI announced Live Search in the API

The new beta (free for a limited time) feature allows apps leveraging Grok models to search real-time info from X and the internet, including news

🔆 t.me/techpsyche

10 Things you need to become an AI/ML engineer:

1. Framing machine learning problems
2. Weak supervision and active learning
3. Processing, training, deploying, inference pipelines
4. Offline evaluation and testing in production
5. Performing error analysis. Where to work next
6. Distributed training. Data and model parallelism
7. Pruning, quantization, and knowledge distillation
8. Serving predictions. Online and batch inference
9. Monitoring models and data distribution shifts
10. Automatic retraining and evaluation of models

5 Free NLP Courses
https://t.me/airesourcestp/110

AI & ML Free Courses by Top Institutions
https://bit.ly/4hCdn45

Best Courses for AI from Universities with YouTube Playlists
https://t.me/airesourcestp/111

Like if you want me to continue data science series 😄❤️

More Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R

ENJOY LEARNING 👍👍

Remote AI Automation Developer Job at Contra

Budget: $40 - $75/hr • 20 hrs/wk

Tech Stack:
* We use Make, Notion, and OpenAI (GPT-4). This isn’t just drag-and-drop automation; you’ll need to understand:
* APIs and JSON
* Regex and parsing logic
* Structuring data for AI input/output
* Debugging complex, multi-branch scenarios
* Code-level thinking when automation complexity increases

Apply Here:
https://kenyatrends.co.ke/m9m8

Global Tech Jobs Here👇
https://t.me/techpsyche

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🇬🇧 AI is taking over weather forecasting

Back in the day, the UK used a room-sized computer named Comet to predict the weather. Now, AI is doing the heavy lifting, and it’s getting freakishly good at it. AI can now spot weather patterns faster, more accurately, and even zoom in to street-level forecasts, like “bring an umbrella for this exact corner.”

Tech giants like Google, Nvidia, and Microsoft are jumping in, while some scientists are building weather AIs that run on laptops, not supercomputers. This is a wild development. However, the catch is that these systems need tons of data, and global budget cuts or political drama could mess that up. Less data means worse forecasts, which could result in you getting soaked without warning. But don’t worry, human meteorologists aren’t getting replaced just yet. Someone still has to sanity-check the numbers and explain when the data doesn’t add up.

🔆 t.me/techpsyche

Money Priorities

✅ Difference Between USDT and USDC

USDT (Tether) and USDC (USD Coin) are both stablecoins pegged to the US Dollar. Here's how they differ: 

1️⃣ Issuers and Backing
- USDT: Issued by Tether Limited, backed by reserves including cash and other assets. Questions about transparency exist. 
- USDC: Issued by Circle in partnership with Coinbase, backed by cash and US Treasury bonds with regular audits. 

2️⃣ Transparency
- USDT: Less transparent; faced scrutiny over reserve accuracy. 
- USDC: More transparent; undergoes monthly third-party audits. 

3️⃣ Regulatory Compliance
- USDT: Operates with fewer regulatory commitments. 
- USDC: Adheres to U.S. financial regulations, trusted by institutions.

4️⃣ Use Cases
- USDT: Popular for trading due to high liquidity. 
- USDC: Preferred for DeFi, payments, and applications needing transparency. 

5️⃣ Adoption
- USDT: Most traded stablecoin globally. 
- USDC: Growing in popularity, especially among institutions. 

6️⃣ Blockchain Support
- USDT: Available on multiple blockchains like Ethereum, Tron, Solana, and more. 
- USDC: Also supports multiple blockchains but slightly less widespread. 

💡 Conclusion:
- Use USDT for liquidity and trading volume. 
- Use USDC for transparency, compliance, and institutional trust. 

Funding in Crypto Trading: https://t.me/techpsyche/766

Choosing the right Exchange: https://t.me/techpsyche/774

Types of Stablecoins: https://t.me/techpsyche/1092

More Resources Here:
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#crypto #web3 #blockchain #finance #stocks

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Tableau Cheat Sheet ✅

This Tableau cheatsheet is designed to be your quick reference guide for data visualization and analysis using Tableau. Whether you’re a beginner learning the basics or an experienced user looking for a handy resource, this cheatsheet covers essential topics.

1. Connecting to Data
- Use Connect pane to connect to various data sources (Excel, SQL Server, Text files, etc.).

2. Data Preparation
- Data Interpreter: Clean data automatically using the Data Interpreter.
- Join Data: Combine data from multiple tables using joins (Inner, Left, Right, Outer).
- Union Data: Stack data from multiple tables with the same structure.

3. Creating Views
- Drag & Drop: Drag fields from the Data pane onto Rows, Columns, or Marks to create visualizations.
- Show Me: Use the Show Me panel to select different visualization types.

4. Types of Visualizations
- Bar Chart: Compare values across categories.
- Line Chart: Display trends over time.
- Pie Chart: Show proportions of a whole (use sparingly).
- Map: Visualize geographic data.
- Scatter Plot: Show relationships between two variables.

5. Filters
- Dimension Filters: Filter data based on categorical values.
- Measure Filters: Filter data based on numerical values.
- Context Filters: Set a context for other filters to improve performance.

6. Calculated Fields
- Create calculated fields to derive new data:
- Example: Sales Growth = SUM([Sales]) - SUM([Previous Sales])

7. Parameters
- Use parameters to allow user input and control measures dynamically.

8. Formatting
- Format fonts, colors, borders, and lines using the Format pane for better visual appeal.

9. Dashboards
- Combine multiple sheets into a dashboard using the Dashboard tab.
- Use dashboard actions (filter, highlight, URL) to create interactivity.

10. Story Points
- Create a story to guide users through insights with narrative and visualizations.

11. Publishing & Sharing
- Publish dashboards to Tableau Server or Tableau Online for sharing and collaboration.

12. Export Options
- Export to PDF or image for offline use.

13. Keyboard Shortcuts
- Show/Hide Sidebar: Ctrl+Alt+T
- Duplicate Sheet: Ctrl + D
- Undo: Ctrl + Z
- Redo: Ctrl + Y

14. Performance Optimization
- Use extracts instead of live connections for faster performance.
- Optimize calculations and filters to improve dashboard loading times.

Tableau Learning Plan
https://t.me/dataanalysisresourcestp/84

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Data Analyst Checklist
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Hope it helps :)

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🚀 Claude 4 is here and it’s a coding beast

Anthropic dropped two new models, and both are seriously impressive:

🟡 Claude Opus 4: the most powerful Claude yet. It writes complex code, plans ahead, runs research, and can work autonomously for hours. Anthropic says it’s the best AI coder in the world.

🟡 Claude Sonnet 4: the everyday powerhouse. Better memory, sharper reasoning, more precise code. Now supports tools like VS Code, web search, and file access — even in free use.

What’s new:
• Parallel tool use
• Extended memory
• File access
• Integration with dev tools (VS Code and JetBrains)

➡️ Best part? Sonnet 4 is already available for free.

🔆 More Updates Here

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UI vs UX

Thread Here: https://t.me/designresourcestp/102

🚀 Boost Your Flutter App Performance!

Flutter is fast, but are you using these tricks to make it even smoother?

✅ Use const widgets – Reduces widget rebuilds.
✅ Avoid unnecessary setState – Only update what’s needed.
✅ Use ListView.builder – For efficient scrolling.
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Complete Flutter Roadmap: https://t.me/mobiledevresourcestp/84

#flutter

Master Data Science & Machine Learning

1️⃣ Basics of Data Science

🏷 Statistics and Probability
◾️ Statistics & Probability (https://www.khanacademy.org/math/statistics-probability)
🏷 Linear Algebra
◽️ Essence of Linear Algebra
(https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)
🏷 Unlimited Resources
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🏷 Python
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(https://www.codecademy.com/learn/learn-python-3)
🏷 Unlimited Resources
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3️⃣ Data Analysis and Manipulation
🏷 Pandas Library
◾️ Pandas Documentation
(https://pandas.pydata.org/pandas-docs/stable/)🏷 Data Preparation with Pandas
◾️ Data Wrangling with Pandas
(https://realpython.com/pandas-dataframe/)🏷 NumPy Library
◾️ NumPy Documentation
(https://numpy.org/doc/stable/)4️⃣ Data Visualization
🏷 Matplotlib and Seaborn Library
◾️ Matplotlib (https://matplotlib.org/stable/users/index.html) / Seaborn (https://seaborn.pydata.org/)
🏷Tableau Public Platform
◾️ Tableau Public
(https://public.tableau.com/app/discover)5️⃣ Principles of Machine Learning
🏷 scikit-learn Library
◾️ scikit-learn
(https://scikit-learn.org/stable/index.html)
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🏷 Hands-On Machine Learning Book
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🏷 Unlimited Resources
◽️ https://t.me/techpsyche
7️⃣ Deep Learning
🏷 TensorFlow Library
◾️ TensorFlow Tutorial
(https://www.tensorflow.org/tutorials)
🏷 PyTorch Library
◾️ PyTorch Documentation
(https://pytorch.org/docs/stable/index.html)
🏷 Unlimited Resources
◽️ https://t.me/mlresourcestp
8️⃣ Big Data Technologies
🏷 Spark Framework Course
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🏷 Unlimited Resources
◽️ https://t.me/datascienceresourcestp
9️⃣ Advanced Topics
🏷 Natural Language Processing Course in Python
◾️ NLP in Python
(https://www.datacamp.com/courses/introduction-to-natural-language-processing-in-python)
🏷 Unlimited Resources
◽️ https://t.me/airesourcestp
1️⃣ Share Your Projects on Kaggle and GitHub
🏷 Kaggle Platform
◾️ Kaggle (https://www.kaggle.com/)
🏷 GitHub Platform
◾️ GitHub (https://github.com/)

Happy Learning! 🌟

Learn DatA & AI: https://365datascience.pxf.io/Z6KDgk

Free Notes & Books to learn Data Science: https://t.me/datascienceresourcestp

Python Project Ideas: https://t.me/pythonresourcestp/74

Best Resources to learn Data Science 👇👇

Python Tutorial (http://pythontutorial.net/)

Data Science Course (http://kaggle.com/learn) by Kaggle

Machine Learning Course (http://developers.google.com/machine-learning/crash-course) by Google

Best Data Science & Machine Learning Resources (https://topmate.io/learning_resources/1406977)

Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/85)

Python Interview Resources (https://t.me/pythonresourcestp/40)

Join for more free courses
https://t.me/techpsyche

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ENJOY LEARNING👍👍
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