https://www.instagram.com/reel/DDCSE7BoNPf/?igsh=azlpcjI0MzBtOXdh

Advanced Camera Control is now available for Gen-3 Alpha Turbo. Choose both the direction and intensity of how you move through your scenes for even more intention in every shot. Available now at runwayml.com

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it’s genius😳, Tesla Bot lying…

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🚀 We're Hiring: hashtag#Technical_Support_Engineer 🚀
📍 Location: Baner, hashtag#Pune
💼 Experience: 2–4 years
📊 Openings: 2 positions

Join our dynamic team and empower businesses with cutting-edge BI solutions and seamless support!

What You’ll Do:
🌐 Systems & Networking: Manage Linux/Unix systems and ensure seamless data flow.
📊 BI & Analytics: Build and maintain dashboards using tools like Incorta, Power BI, Tableau, and more.
☁️ Cloud Integration: Support cloud platforms (AWS, Azure, GCP).
💾 SQL & Data Integration: Optimize data processes and analytics solutions.

What We’re Looking For:
🔑 Expertise in Linux/Unix systems and networking.
📈 Hands-on experience with BI tools and SQL.
☁️ Familiarity with cloud platforms (AWS, Azure, GCP).
🚀 Bonus: Java application support and data warehousing experience.

💡 Why Join Us?
Collaborate on impactful projects.
Grow with cutting-edge technologies.
Be part of a team that values innovation and problem-solving.
Ready to take your career to the next level? Apply now and let’s make data-driven magic together!

Share your CV at anmolj@ithena.ai

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We are hiring : Data Scientist
Location- Noida (WFO)

Required Skills and Qualifications:
Experience: 3-5 years of experience in Data Science, AI, and Machine Learning.
Proficiency in Python, R, or other relevant programming languages.
Expertise in LLM fine-tuning, prompt engineering, and vector databases.
Experience with frameworks like LangChain, Hugging Face Transformers, or similar tools.
Strong knowledge of retrieval systems and knowledge bases for RAG pipelines.
Hands-on experience in deploying models in cloud environments like AWS, GCP, or Azure.

Interested candidates please share your CV at vaishali.tyagi@kiwitech.com

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12 Papers You Should Read to Understand Object Detection in the Deep Learning Era

https://towardsdatascience.com/12-papers-you-should-read-to-understand-object-detection-in-the-deep-learning-era-3390d4a28891

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Only playlist you need to look to learn Machine Learning from Basics

https://youtube.com/playlist?list=PL9m8ngZLLVomZCPblj4Py7HpQapy5dlfB&si=5p0auz1fYVzikpJr

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🚀 𝐅𝐥𝐚𝐢𝐫𝐬𝐓𝐞𝐜𝐡 𝐢𝐬 𝐇𝐢𝐫𝐢𝐧𝐠: 𝐉𝐮𝐧𝐢𝐨𝐫 𝐌𝐋/𝐀𝐈/𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭 - 𝐅𝐮𝐥𝐥-𝐓𝐢𝐦𝐞 (𝐂𝐚𝐢𝐫𝐨) 🚀

𝐖𝐡𝐚𝐭 𝐘𝐨𝐮’𝐥𝐥 𝐁𝐫𝐢𝐧𝐠:
✅ Python Skills: Proficiency with libraries like NumPy, pandas, and scikit-learn.
✅ API Development: Basic experience with FastAPI for creating web services.
✅ Database Knowledge: Familiarity with SQL or MongoDB.
✅ DevOps Basics: Exposure to Docker, CI/CD, and cloud technologies is a plus.
✅ Error Tracking: Understanding logging and troubleshooting techniques.
✅ AI Foundations: Interest or experience in NLP (e.g., NLTK) or computer vision (e.g., OpenCV).

𝐀𝐩𝐩𝐥𝐲 𝐍𝐨𝐰:
📩 Send your CV to habeba.kamel@flairstech.com with the subject line "Junior ML/AI/Data Scientist Position."

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Mathematical Foundations of Machine Learning

📓 book

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Are They the Same? Exploring Visual Correspondence Shortcomings of Multimodal LLMs

🖥 Github: https://github.com/zhouyiks/CoLVA/tree/main

📕 Paper: https://arxiv.org/pdf/2501.04670v1.pdf

⭐️ Dataset: https://paperswithcode.com/dataset/bdd100k

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DeepMind in collaboration with University College London "Reinforcement Learning Lecture Series 2021"

Website: https://lnkd.in/gwykwSAy
Video lectures: https://lnkd.in/gJxaQXic

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Guide to Building an AI Agent

1️⃣ 𝗖𝗵𝗼𝗼𝘀𝗲 𝘁𝗵𝗲 𝗥𝗶𝗴𝗵𝘁 𝗟𝗟𝗠
Not all LLMs are equal. Pick one that:
- Excels in reasoning benchmarks
- Supports chain-of-thought (CoT) prompting
- Delivers consistent responses

📌 Tip: Experiment with models & fine-tune prompts to enhance reasoning.

2️⃣ 𝗗𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝗔𝗴𝗲𝗻𝘁’𝘀 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗟𝗼𝗴𝗶𝗰
Your agent needs a strategy:
- Tool Use: Call tools when needed; otherwise, respond directly.
- Basic Reflection: Generate, critique, and refine responses.
- ReAct: Plan, execute, observe, and iterate.
- Plan-then-Execute: Outline all steps first, then execute.

📌 Choosing the right approach improves reasoning & reliability.

3️⃣ 𝗗𝗲𝗳𝗶𝗻𝗲 𝗖𝗼𝗿𝗲 𝗜𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗶𝗼𝗻𝘀 & 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀
Set operational rules:
- How to handle unclear queries? (Ask clarifying questions)
- When to use external tools?
- Formatting rules? (Markdown, JSON, etc.)
- Interaction style?

📌 Clear system prompts shape agent behavior.

4️⃣ 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁 𝗮 𝗠𝗲𝗺𝗼𝗿𝘆 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆
LLMs forget past interactions. Memory strategies:
- Sliding Window: Retain recent turns, discard old ones.
- Summarized Memory: Condense key points for recall.
- Long-Term Memory: Store user preferences for personalization.

📌 Example: A financial AI recalls risk tolerance from past chats.

5️⃣ 𝗘𝗾𝘂𝗶𝗽 𝘁𝗵𝗲 𝗔𝗴𝗲𝗻𝘁 𝘄𝗶𝘁𝗵 𝗧𝗼𝗼𝗹𝘀 & 𝗔𝗣𝗜𝘀
Extend capabilities with external tools:
- Name: Clear, intuitive (e.g., "StockPriceRetriever")
- Description: What does it do?
- Schemas: Define input/output formats
- Error Handling: How to manage failures?

📌 Example: A support AI retrieves order details via CRM API.

6️⃣ 𝗗𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝗔𝗴𝗲𝗻𝘁’𝘀 𝗥𝗼𝗹𝗲 & 𝗞𝗲𝘆 𝗧𝗮𝘀𝗸𝘀
Narrowly defined agents perform better. Clarify:
- Mission: (e.g., "I analyze datasets for insights.")
- Key Tasks: (Summarizing, visualizing, analyzing)
- Limitations: ("I don’t offer legal advice.")

📌 Example: A financial AI focuses on finance, not general knowledge.

7️⃣ 𝗛𝗮𝗻𝗱𝗹𝗶𝗻𝗴 𝗥𝗮𝘄 𝗟𝗟𝗠 𝗢𝘂𝘁𝗽𝘂𝘁𝘀
Post-process responses for structure & accuracy:
- Convert AI output to structured formats (JSON, tables)
- Validate correctness before user delivery
- Ensure correct tool execution

📌 Example: A financial AI converts extracted data into JSON.

8️⃣ 𝗦𝗰𝗮𝗹𝗶𝗻𝗴 𝘁𝗼 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 (𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱)
For complex workflows:
- Info Sharing: What context is passed between agents?
- Error Handling: What if one agent fails?
- State Management: How to pause/resume tasks?

📌 Example:
1️⃣ One agent fetches data
2️⃣ Another summarizes
3️⃣ A third generates a report

Master the fundamentals, experiment, and refine and.. now go build something amazing! (Written by : Armand Ruiz)
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Only playlist you need to look to learn Machine Learning from Basics

https://youtube.com/playlist?list=PL9m8ngZLLVomZCPblj4Py7HpQapy5dlfB&si=5p0auz1fYVzikpJr

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This free 8 hour course from NVIDIA is all you need to start building RAG Agents with LLMs

It talks in depth about -

- LLM Inference Interfaces
- Pipeline Design with LangChain
- Gradio and LangServe
- Dialog Management with Running States
- Working with Documents
- Embeddings for Semantic Similarity and Guardrailing
- Vector Stores for RAG Agents

Start your course here -

https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-15+V1

🚀 *We’re Hiring: Data Analyst Trainer | Udaipur* 📊

Are you passionate about data analysis and excited to share your expertise with future professionals? We are looking for a *Data Analyst Trainer* to join our team in *Udaipur, Rajasthan*!

If you have practical experience in *Python*, *Power BI*, and *Advanced Excel*, along with a flair for teaching and mentoring, we’d love to hear from you!

🔍 *Position*: Data Analyst Trainer
📍 *Location*: Udaipur, Rajasthan
🕒 *Experience*: Minimum 1 year of training experience
💰 *Salary*: ₹3 LPA to ₹5.4 LPA

*Qualifications*:
✅ Degree or Diploma in *Computer Science*, *IT*, or related fields
✅ Strong hands-on knowledge of *Python*, *Power BI*, and *Advanced Excel*
✅ Ability to simplify and communicate complex data analysis concepts effectively

*Skills*:
💡 Excellent *teaching* & *presentation* skills
💡 In-depth knowledge of *Python*, *Power BI*, and *Excel*
💡 Ability to engage and inspire students to master data analysis tools and techniques

🚀 Be a part of our mission to shape the next generation of data professionals!

📩 *Interested?* Send your CV to *akash@certedtechnologies.com* or contact *7748888320* for more information.

Let's make data analysis fun and engaging together! 📊✨

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