Most of the big organizations are struggling with AI transformation. Data science projects are either taking too long to complete or would never get into production.
Among various reasons, the most common is the lack of a stable data science team. Due to high demand, the turnover rate is very high in data science, unfortunately. Data science managers or leaders typically go around this problem by focusing on the following:
Added by Nasir Mahmood on May 5, 2020 at 1:30am — No Comments
With increased digitization comes the need for infrastructural stability and safety. That’s where TensorFlow can provide maximum returns, especially in the road safety domain. On-road traffic accidents can be minimized with greater efficiencies in overall traffic management. There is also greater control and oversight when dealing with multiple vehicles across various roads.…Continue
Added by Amit Dua on March 28, 2019 at 12:07am — No Comments
The shortage of data scientists is a hindrance to the widespread adoption of analytics across many industries.
At the same time, the preponderance of multiple tools, techniques and knowledge base along with the rapidly changing data science landscape make it difficult for analytics leaders to hire the right talent for their data science team. The attrition rate in this industry is also high due to which employers end up spending a lot of time and money to hire a data…Continue
Added by Aatash Shah on November 7, 2016 at 4:30am — No Comments
Did you know that athletes are not only monitored by cameras on stadiums, but also by many quirky devices such as accelerometers, heart rate sensors and even local GPS-like systems? Indeed, Big Data and modern technologies are currently revolutionizing sports and even powering the Fantasy Sports…Continue