Having an innovative culture is healthy for the growth of the organisation. There are always forces that pull you into short term initiatives. But companies need a push forward to steer towards the long term initiatives as well. Innovation acts as a force multiplier for any team and simultaneously maintains the enthusiasm, energy and excitement of the overall team.
The key thing to remember is that we need a governance process but, at the same time, innovation and experimentation cannot be stifled. Finding a process that ensures robust and reliable data science models while encouraging learning and out-of-the-box thinking is at the heart of the model governance process.
The challenge and the temptation to try to apply these models to real-world problems are very significant. The complexity can get very deceptive and lead to suboptimal outcomes. The speed of building something complex often outweighs the solution’s usefulness
In most organisations, the objective and key results, hiring plan, delivery and performance management are data-driven.
The skills needed for a HoDS include technical knowledge and problem-solving; the ability to build and nurture teams; focus on delivery, stakeholders, strategic thinking and executive presence.
The AI team consists of ‘an external team’ (a team external to the data team but part of the core AI team) that works closely with the data team and then there is the core data team itself.
AI has become the next big innovation that established companies and start-up organisations are fighting to integrate into their structure. The demand is due to
With the world becoming smarter and more data inclined, it has become essential for start-ups to leverage data. Data not only gives them a competitive
Research in Deep Learning started as early as the 1960s, though the term itself was coined in 1986. With accurate predictions becoming the need of
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