Artificial Intelligence | AI Tools | Coding Books
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๐Ÿ”“Unlock Your Coding Potential with ChatGPT
๐Ÿš€ Your Ultimate Guide to Ace Coding Interviews!
๐Ÿ’ป Coding tips, practice questions, and expert advice to land your dream tech job.


For Promotions: @love_data
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Useful Resources to learn AI/ML ๐Ÿ‘†
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๐—ง๐—ผ๐—ฝ ๐— ๐—ก๐—–๐˜€ ๐—›๐—ถ๐—ฟ๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜€๐˜๐˜€ ๐Ÿ˜

- Capgemini 
- Infosys
- KPMG
- Genpact
- JP Morgan

Qualification :- Any Graduate 

๐‘๐ž๐ ๐ข๐ฌ๐ญ๐ž๐ซ & ๐”๐ฉ๐ฅ๐จ๐š๐ ๐˜๐จ๐ฎ๐ซ ๐‘๐ž๐ฌ๐ฎ๐ฆ๐ž๐Ÿ‘‡:-  

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Enter your experience & Complete The Registration Process

Select the company name & Apply for jobs
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Python vs C++ vs Java ๐Ÿ˜‚
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๐—Ÿ๐—ฒ๐—ฎ๐—ฟ๐—ป ๐—”๐—œ, ๐——๐—ฒ๐˜€๐—ถ๐—ด๐—ป & ๐—ฃ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜ ๐— ๐—ฎ๐—ป๐—ฎ๐—ด๐—ฒ๐—บ๐—ฒ๐—ป๐˜ ๐—ณ๐—ผ๐—ฟ ๐—™๐—ฅ๐—˜๐—˜!๐Ÿ˜

Want to break into AI, UI/UX, or project management? ๐Ÿš€

These 5 beginner-friendly FREE courses will help you develop in-demand skills and boost your resume in 2025!๐ŸŽŠ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

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โœจ No cost, no catchโ€”just pure learning from anywhere!
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Tips for working with Microsoft
Word


โœ… To quickly insert the current date, press SHIFT + ALT + D, and to insert the time, SHIFT + ALT + T.

โœ… If you accidentally typed a text with the CAPS LOCK key enabled, then select the text in uppercase and press SHIFT + F3.

โœ… To speed up the cursor movement through the text, hold down CTRL and use the arrows.

โœ… By holding CTRL, you can select all the parts of the text you are interested in, even if they are not arranged in a row.

โœ… The F4 key repeats the last command used.

โœ… Place the cursor at the beginning of the text selection and click at the end of the desired text segment with the SHIFT key held down for quick selection.

โœ… Press CTRL + ENTER to quickly create a new sheet.

#lifehack #windows
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๐—ฃ๐—ฟ๐—ฒ๐—บ๐—ถ๐˜‚๐—บ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐Ÿ˜

- Python Programming
- Data Analytics 
- Generative AI
- Machine Learning 
- Data Science 
- SQL

๐‹๐ข๐ง๐ค ๐Ÿ‘‡:-

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Enroll Now & Get a course completion certificate๐ŸŽ“
Anthropicโ€™s AI assistant Claude learns to search the web

Anthropic has announced its AI assistant Claude can now search the web, providing users with more up-to-date and relevant responses.

This integration of web search functionality means Claude can now access the latest information to expand its knowledge base beyond its initial training data.

A key feature of this update is the emphasis on transparency and fact-checking. Anthropic highlights that โ€œWhen Claude incorporates information from the web into its responses, it provides direct citations so you can easily fact check sources.โ€
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Data Analyst Roadmap ๐Ÿ’ช
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๐—ฆ๐˜๐—ฟ๐˜‚๐—ด๐—ด๐—น๐—ถ๐—ป๐—ด ๐˜„๐—ถ๐˜๐—ต ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—•๐—œ? ๐—ง๐—ต๐—ถ๐˜€ ๐—–๐—ต๐—ฒ๐—ฎ๐˜ ๐—ฆ๐—ต๐—ฒ๐—ฒ๐˜ ๐—ถ๐˜€ ๐—ฌ๐—ผ๐˜‚๐—ฟ ๐—จ๐—น๐˜๐—ถ๐—บ๐—ฎ๐˜๐—ฒ ๐—ฆ๐—ต๐—ผ๐—ฟ๐˜๐—ฐ๐˜‚๐˜!๐Ÿ˜

Mastering Power BI can be overwhelming, but this cheat sheet by DataCamp makes it super easy! ๐Ÿš€

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/4ld6F7Y

No more flipping through tabs & tutorialsโ€”just pin this cheat sheet and analyze data like a pro!โœ…๏ธ
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Best free resources to learn AI ๐Ÿ˜ป๐Ÿ™Œ
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How long are coding interviews?
The phone screen portion of the coding interview typically lasts up to one hour. The second, more technical part of the interview can take multiple hours.

Where can I practice coding?
There are many ways to practice coding and prepare for your coding interview. LeetCode provides practice opportunities in more than 14 languages and more than 1,500 sample problems. Applicants can also practice their coding skills and interview prep with HackerRank.

How do I know if my coding interview went well?
There are a variety of indicators that your coding interview went well. These may include going over the allotted time, being introduced to additional team members, and receiving a quick response to your thank you email.
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๐—™๐—ฅ๐—˜๐—˜ ๐—ข๐—ป๐—น๐—ถ๐—ป๐—ฒ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ๐—ฐ๐—น๐—ฎ๐˜€๐˜€ ๐—ข๐—ป ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ ๐Ÿ˜ 

Data Science is reshaping industries, and having the right tools and skills can set you apart in this exciting field

Know The Roadmap To Become a Successful Data Scientist In 2025

Eligibility :- Students, Graduates & Woking Professionals 

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๐ƒ๐š๐ญ๐ž & ๐“๐ข๐ฆ๐ž:-  29th March, 2025, at 7 PM
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7 level of writing Python Dictionary



Level 1: Basic Dictionary Creation

Level 2: Accessing and Modifying values

Level 3: Adding and Removing key Values Pairs

Level 4: Dictionary Methods

Level 5: Dictionary Comprehensions

Level 6: Nested Dictionary

Level 7: Advanced Dictionary Operations

I have curated the best interview resources to crack Python Interviews ๐Ÿ‘‡๐Ÿ‘‡
https://topmate.io/coding/898340

Hope you'll like it

Like this post if you need more resources like this ๐Ÿ‘โค๏ธ
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Artificial intelligence can change your career by 180 degrees! ๐Ÿ“Œ

Here's how you can start with AI engineering with zero experience!

The simplest definition of artificial intelligence|

Artificial intelligence (AI) is a part of computer science that creates smart systems to solve problems usually needing human intelligence.

AI includes tasks like recognizing objects and patterns, understanding voices, making predictions, and more.

Step 1: Master the prerequisites

Basics of programming
Probability and statistics essentials
Data structures
Data analysis essentials

Step 2: Get into machine learning and deep learning

Basics of data science, an intersection field
Feature engineering and machine learning
Neural networks and deep learning
Scikit-learn for machine learning along with Numpy, Pandas and matplotlib
TensorFlow, Keras and PyTorch for deep learning

Step 3: Exploring Generative Adversarial Networks (GANs)

Learn GAN fundamentals: Understand the theory behind GANs, including how the generator and discriminator work together to produce realistic data.

Hands-on projects: Build and train simple GANs using PyTorch or TensorFlow to generate images, enhance resolution, or perform style transfer.

Step 4: Get into Transformers architecture

Grasp the basics: Study the Transformer architecture's key concepts, including attention mechanisms, positional encodings, and the encoder-decoder structure.
Implementations: Use libraries like Hugging Faceโ€™s Transformers to experiment with different Transformer models, such as GPT and BERT, on NLP tasks.

Step 5: Working with Pre-trained Large Language Models

Utilize existing models: Learn how to leverage pre-trained models from libraries like Hugging Face to perform tasks like text generation, translation, and sentiment analysis.

Fine-tuning techniques: Explore strategies for fine-tuning these models on domain-specific datasets to improve performance and relevance.

Step 6: Introduction to LangChain

Understand LangChain: Familiarize yourself with LangChain, a framework designed to build applications that combine language models with external knowledge and capabilities.

Build applications: Use LangChain to develop applications that interactively use language models to process and generate information based on user queries or tasks.

Step 7: Leveraging Vector Databases

Basics of vector databases: Understand what vector databases are and why they are crucial for managing high-dimensional data typically used in AI models.
Tools and technologies: Learn to use vector databases like Milvus, Pinecone, or Weaviate, which are optimized for fast similarity search and efficient handling of vector embeddings.
Practical application: Integrate vector databases into your projects for enhanced search functionalities

Step 8: Exploration of Retrieval-Augmented Generation (RAG)

Learn the RAG approach: Understand how RAG models combine the power of retrieval (extracting information from a large database) with generative models to enhance the quality and relevance of the outputs.

Practical applications: Study case studies or research papers that showcase the use of RAG in real-world applications.

Step 9: Deployment of AI Projects

Deployment tools: Learn to use tools like Docker for containerization, Kubernetes for orchestration, and cloud services (AWS, Azure, Google Cloud) for deploying models.

Monitoring and maintenance: Understand the importance of monitoring AI systems post-deployment and how to use tools like Prometheus, Grafana, and Elastic Stack for performance tracking and logging.

Step 10: Keep building

Implement Projects and Gain Practical Experience

Work on diverse projects: Apply your knowledge to solve problems across different domains using AI, such as natural language processing, computer vision, and speech recognition.

Contribute to open-source: Participate in AI projects and contribute to open-source communities to gain experience and collaborate with others.

Hope this helps you โ˜บ๏ธ
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๐Ÿง  How to Use ChatGPT for SEO ?

ChatGPT is a powerful tool to streamline and enhance your SEO efforts, but itโ€™s only as good as the strategy behind it.
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