Your AI project is falling short of expectations. How will you navigate this setback?
Embarking on an AI project can be a thrilling journey, but what happens when your results aren't living up to the hype? It's a common scenario that can leave you feeling deflated. However, this isn't the end of the road. Navigating through setbacks is part of the process, and with the right approach, you can steer your AI project back on track. Whether it's recalibrating your goals, scrutinizing your data, or enhancing your algorithms, there are actionable steps you can take. You'll need to reassess, adapt, and learn from the experience to overcome these hurdles. Remember, the field of AI is as much about resilience and problem-solving as it is about technology.
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Jyothish NairDoctoral Candidate(๐๐ ๐๐ง๐ ๐ญ๐ก๐ ๐ ๐ฎ๐ญ๐ฎ๐ซ๐ ๐จ๐ ๐๐จ๐ซ๐ค ๐ข๐ง ๐๐๐๐ก ๐๐ง๐๐ฎ๐ฌ๐ญ๐ซ๐ฒ) | Technical Deliveryโฆ
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Dr. Sreejit ChakrabartyDirector of AI @ GEMS Education | FORBES 30 Under 30 speaker | BRIGHTCHAMPS Advisory Board member | BETT MEA Advisoryโฆ
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Mohammed BahageelData Scientist / Data Analyst | Machine Learning | Deep Learning | Artificial Intelligence | Data Analyticsโฆ