Last updated on 15 de set. de 2024

Sua equipe está dividida em uma nova estrutura de aprendizado de máquina. Como você vai navegar nessa decisão crítica?

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Marco Narcisi

CEO | Founder | AI Developer at AIFlow.ml | Google and IBM Certified AI Specialist | LinkedIn AI and Machine Learning…
Vipin Thazhissery

Software Architect | Machine Learning Enthusiast | AI Engineer | Business Strategist | Author - The Wrong Right Track

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Daniel Mafla

📣 LinkedIn Top Voice (AI) | CEO Impartum Partner | AI - Consultant and Researcher | Board Member | I+D | Management |…

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Navegar pelas divisões da equipe pode ser complicado. Compartilhe suas estratégias para a tomada de decisões quando as opiniões se chocam.

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Marco Narcisi

CEO | Founder | AI Developer at AIFlow.ml | Google and IBM Certified AI Specialist | LinkedIn AI and Machine Learning Top Voice | Python Developer | Prompt Engineering | LLM | Writer
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When your team is split on adopting a new machine learning framework, navigating the decision requires a structured, collaborative approach. Start by facilitating an open discussion where each team member can present their perspective, highlighting the pros and cons of the framework in question. Encourage data-driven decision-making by evaluating the framework based on key factors like performance, scalability, ease of integration, and long-term support. You can also consider running small pilot projects to assess its impact on your specific use case. Balancing technical merit with team consensus fosters a decision that is informed, practical, and supported by everyone.

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Vipin Thazhissery

Software Architect | Machine Learning Enthusiast | AI Engineer | Business Strategist | Author - The Wrong Right Track
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Facilitate open, constructive discussions where everyone can share their perspectives. As a leader, prioritize active listening and ensure that all voices are heard to foster a collaborative environment. Then, guide the team in making an evidence-based decision by evaluating each framework's performance, scalability, and alignment with long-term goals using objective metrics. If disagreements persist, consider a proof-of-concept phase to test both frameworks on a smaller scale. This hands-on approach can provide valuable insights and help the team reach a consensus. Once a decision is made, it’s crucial for the entire team to fully commit and stay focused on the ultimate goal.

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Daniel Mafla

📣 LinkedIn Top Voice (AI) | CEO Impartum Partner | AI - Consultant and Researcher | Board Member | I+D | Management | Executive Mentoring | Retail Consultant |
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The key is to gather objective data and align the decision with project goals. Start by evaluating each framework based on performance, scalability, ease of integration, and community support. Organize a discussion where each side can present the pros and cons, and use benchmarks or small pilot projects to test the frameworks in real-world scenarios. Encourage the team to focus on long-term benefits and how the framework aligns with your specific needs. By basing the decision on data and practical tests, you can guide the team towards consensus and make an informed choice.

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Diogo Pereira Coelho

Founding Partner @Sypar | Lawyer | PhD Student | Web3 & Web4 | FinTech | DeFi | DLT | DAO | Tokenization | CBDC | Metaverse | AI | CryptoTax | CyberCrime
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To navigate, assess the framework's long-term scalability, compatibility with current tools, and potential for reducing technical debt. Conduct a cost-benefit analysis and pilot tests to gather empirical evidence, fostering a consensus. Open discussions to ensure the team's concerns are heard and addressed.

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Muhammad Rayyan

🚀 Exploring new AI Frontiers | ML | DL | NLP | CV | Data Science | Generative AI | MAS with LLMs | AGI Enthusiast 🤖 | Astrophysics Enthusiast 🌌 | NUST'25 | Let's innovate together 💡
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Team is divided into ML framework, which one to choose. Resolving this step is crucial for successful project completion. Here are strategies which you can follow: - Encourage open dialogue where team members can present their thoughts about the framework they want to choose. - In a meeting invite senior members to critically look into the presentations given by team members and analyze which approach will be best. - Look into real world projects which are completed using same frameworks and how successful they are, for getting an idea.

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