๐ฑ ๐ฃ๐ผ๐๐ฒ๐ฟ๐ณ๐๐น ๐๐ฟ๐ฒ๐ฒ ๐๐ ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐ณ๐ฟ๐ผ๐บ ๐๐ฎ๐ฟ๐๐ฎ๐ฟ๐ฑ & ๐ฆ๐๐ฎ๐ป๐ณ๐ผ๐ฟ๐ฑ๐
Want to learn AI from the best without spending a rupee?
These 5 FREE courses from Harvard and Stanford will help you understand Artificial Intelligence, Deep Learning, NLP, and moreโstraight from the experts๐
๐๐ข๐ง๐ค๐:-
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๐ Learn from the Best, for Free
Want to learn AI from the best without spending a rupee?
These 5 FREE courses from Harvard and Stanford will help you understand Artificial Intelligence, Deep Learning, NLP, and moreโstraight from the experts๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/4lphMdX
๐ Learn from the Best, for Free
10 Must-Know Python Libraries for LLMs in 2025
1. Hugging Face Transformers
Best for: Pre-trained LLMs, fine-tuning, inference
2. LangChain
Best for: LLM-powered apps, chatbots, AI agents
3. SpaCy
Best for: Tokenization, named entity recognition (NER), dependency parsing
4. Natural Language Toolkit (NLTK)
Best for: Linguistic analysis, tokenization, POS tagging
5. SentenceTransformers
Best for: Semantic search, similarity, clustering
6. FastText
Best for: Word embeddings, text classification
7. Gensim
Best for: Word2Vec, topic modeling, document embeddings
8. Stanza
Best for: Named entity recognition (NER), POS tagging
9. TextBlob
Best for: Sentiment analysis, POS tagging, text processing
10. Polyglot
Best for: Multi-language NLP, named entity recognition, word embeddings
1. Hugging Face Transformers
Best for: Pre-trained LLMs, fine-tuning, inference
2. LangChain
Best for: LLM-powered apps, chatbots, AI agents
3. SpaCy
Best for: Tokenization, named entity recognition (NER), dependency parsing
4. Natural Language Toolkit (NLTK)
Best for: Linguistic analysis, tokenization, POS tagging
5. SentenceTransformers
Best for: Semantic search, similarity, clustering
6. FastText
Best for: Word embeddings, text classification
7. Gensim
Best for: Word2Vec, topic modeling, document embeddings
8. Stanza
Best for: Named entity recognition (NER), POS tagging
9. TextBlob
Best for: Sentiment analysis, POS tagging, text processing
10. Polyglot
Best for: Multi-language NLP, named entity recognition, word embeddings
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๐ฏ ๐๐ฟ๐ฒ๐ฒ ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐๐ผ ๐๐ฒ๐๐ฒ๐น ๐จ๐ฝ ๐ฌ๐ผ๐๐ฟ ๐ง๐ฒ๐ฐ๐ต ๐ฆ๐ธ๐ถ๐น๐น๐ ๐ถ๐ป ๐ฎ๐ฌ๐ฎ๐ฑ๐
Want to build your tech career without breaking the bank?๐ฐ
These 3 completely free courses are all you need to begin your journey in programming and data analysis๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3EtHnBI
Learn at your own pace, sharpen your skills, and showcase your progress on LinkedIn or your resume. Letโs dive in!โ ๏ธ
Want to build your tech career without breaking the bank?๐ฐ
These 3 completely free courses are all you need to begin your journey in programming and data analysis๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3EtHnBI
Learn at your own pace, sharpen your skills, and showcase your progress on LinkedIn or your resume. Letโs dive in!โ ๏ธ
How to Learn API Development?
Learning how to develop APIs is an important skill for modern-day developers. Hereโs a mind map of what all you need to learn about API development:
1 - API Fundamentals
What is an API, types of API (REST, SOAP, GraphQL, gRPC, etc.), and API vs SDK.
2 - API Request/Response
HTTP Methods, Response Codes, and Headers.
3 - Authentication and Security
Authentication mechanisms (JWT, OAuth 2, API Keys, Basic Auth) and security strategies.
4 - API Design and Development
RESTful API principles include stateless, resource-based URL, versioning, and pagination. Also, API documentation tools like OpenAPI, Postman, Swagger.
5 - API Testing
Tools for testing APIs such as Postman, cURL, SoapUI, and so on.
6 - API Deployment and Integration
Consuming APIs in different languages like JS, Python, and Java. Also, working with 3rd party APIs like the Google Maps API and the Stripe API. Learn about API Gateways like AWS, Kong, Apigee.
Over to you: What else will you add to the list for learning API development?
Learning how to develop APIs is an important skill for modern-day developers. Hereโs a mind map of what all you need to learn about API development:
1 - API Fundamentals
What is an API, types of API (REST, SOAP, GraphQL, gRPC, etc.), and API vs SDK.
2 - API Request/Response
HTTP Methods, Response Codes, and Headers.
3 - Authentication and Security
Authentication mechanisms (JWT, OAuth 2, API Keys, Basic Auth) and security strategies.
4 - API Design and Development
RESTful API principles include stateless, resource-based URL, versioning, and pagination. Also, API documentation tools like OpenAPI, Postman, Swagger.
5 - API Testing
Tools for testing APIs such as Postman, cURL, SoapUI, and so on.
6 - API Deployment and Integration
Consuming APIs in different languages like JS, Python, and Java. Also, working with 3rd party APIs like the Google Maps API and the Stripe API. Learn about API Gateways like AWS, Kong, Apigee.
Over to you: What else will you add to the list for learning API development?
๐5
๐๐ & ๐ ๐ ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐
Qualcommโa global tech giant offering completely FREE courses that you can access anytime, anywhere.
โ 100% Free โ No hidden charges, subscriptions, or trials
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๐๐ข๐ง๐ค ๐:-
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Enroll Now & Get Certified ๐
Qualcommโa global tech giant offering completely FREE courses that you can access anytime, anywhere.
โ 100% Free โ No hidden charges, subscriptions, or trials
โ Created by Industry Experts
โ Self-paced & Online โ Learn from anywhere, anytime
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/3YrFTyK
Enroll Now & Get Certified ๐
To start with Machine Learning:
1. Learn Python
2. Practice using Google Colab
Take these free courses:
https://t.me/datasciencefun/290
If you need a bit more time before diving deeper, finish the Kaggle tutorials.
At this point, you are ready to finish your first project: The Titanic Challenge on Kaggle.
If Math is not your strong suit, don't worry. I don't recommend you spend too much time learning Math before writing code. Instead, learn the concepts on-demand: Find what you need when needed.
From here, take the Machine Learning specialization in Coursera. It's more advanced, and it will stretch you out a bit.
The top universities worldwide have published their Machine Learning and Deep Learning classes online. Here are some of them:
https://t.me/datasciencefree/259
Many different books will help you. The attached image will give you an idea of my favorite ones.
Finally, keep these three ideas in mind:
1. Start by working on solved problems so you can find help whenever you get stuck.
2. ChatGPT will help you make progress. Use it to summarize complex concepts and generate questions you can answer to practice.
3. Find a community on LinkedIn or ๐ and share your work. Ask questions, and help others.
During this time, you'll deal with a lot. Sometimes, you will feel it's impossible to keep up with everything happening, and you'll be right.
Here is the good news:
Most people understand a tiny fraction of the world of Machine Learning. You don't need more to build a fantastic career in space.
Focus on finding your path, and Write. More. Code.
That's how you win.โ๏ธโ๏ธ
1. Learn Python
2. Practice using Google Colab
Take these free courses:
https://t.me/datasciencefun/290
If you need a bit more time before diving deeper, finish the Kaggle tutorials.
At this point, you are ready to finish your first project: The Titanic Challenge on Kaggle.
If Math is not your strong suit, don't worry. I don't recommend you spend too much time learning Math before writing code. Instead, learn the concepts on-demand: Find what you need when needed.
From here, take the Machine Learning specialization in Coursera. It's more advanced, and it will stretch you out a bit.
The top universities worldwide have published their Machine Learning and Deep Learning classes online. Here are some of them:
https://t.me/datasciencefree/259
Many different books will help you. The attached image will give you an idea of my favorite ones.
Finally, keep these three ideas in mind:
1. Start by working on solved problems so you can find help whenever you get stuck.
2. ChatGPT will help you make progress. Use it to summarize complex concepts and generate questions you can answer to practice.
3. Find a community on LinkedIn or ๐ and share your work. Ask questions, and help others.
During this time, you'll deal with a lot. Sometimes, you will feel it's impossible to keep up with everything happening, and you'll be right.
Here is the good news:
Most people understand a tiny fraction of the world of Machine Learning. You don't need more to build a fantastic career in space.
Focus on finding your path, and Write. More. Code.
That's how you win.โ๏ธโ๏ธ
๐3
Forwarded from Generative AI
๐๐ฃ ๐ ๐ผ๐ฟ๐ด๐ฎ๐ป ๐๐ฅ๐๐ ๐ฉ๐ถ๐ฟ๐๐๐ฎ๐น ๐๐ป๐๐ฒ๐ฟ๐ป๐๐ต๐ถ๐ฝ ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ๐๐
JPMorgan offers free virtual internships to help you develop industry-specific tech, finance, and research skills.
- Software Engineering Internship
- Investment Banking Program
- Quantitative Research Internship
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/4gHGofl
Enroll For FREE & Get Certified ๐
JPMorgan offers free virtual internships to help you develop industry-specific tech, finance, and research skills.
- Software Engineering Internship
- Investment Banking Program
- Quantitative Research Internship
๐๐ข๐ง๐ค ๐:-
https://pdlink.in/4gHGofl
Enroll For FREE & Get Certified ๐
๐ง๐ผ๐ฝ ๐ ๐ก๐๐ ๐๐ถ๐ฟ๐ถ๐ป๐ด ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐๐ ๐
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TechM :- https://pdlink.in/4cws0oN
SE :- https://pdlink.in/42feu5D
Siemens :- https://pdlink.in/4jxhzDR
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EY:- https://pdlink.in/4lwMQZo
Apply before the link expires ๐ซ
๐1