Shenzhi Shi on AI and Data AnalyticsData Analytics | AI | Innovation Lead | Social EntrepreneurSome time ago
Action!Action!Action! - the secret key of value generating data analytics
To create real value by using AI and big data in your decision making, the key is that you should always start with an Action hypothesis.
Instead of asking: what can we know from these datasets? You should ask: what alternatives do I have, what information do I need to have to make my choice, and what would be the consequences?
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Be the first to commentShenzhi Shi on AI and Data AnalyticsData Analytics | AI | Innovation Lead | Social EntrepreneurSome time ago
AI isn’t the solution for everything!
Most of the time, you don’t need AI AT ALL!
AI is merely one of the technical solutions to tackle our problems.
Problems happened not just because of lack of certain technology. A lot of times, it’s about human cooperation, mindsets, skills, process, governance, or lack of clear leadership... etc.
The very first step before you jump into the question how should I solve the problem: you should always spend a good amount of time on understanding your problem.
You need to ask yourself and the key people around you:
Are you solving the right problem?
What’s the root cause of that problem?
Then, after you have clearer picture about what’s really going wrong, then we can think about what could be the best and most sustainable way to tackle it.
Andrew Lim Mao TungWindows System Admin with a passion to motivate and likes Technology.
Totally agreed, all it because of human cooperation, mindset etc.
When I was young and in school, I told myself not to get involved in relationships with girls, seeing how my parents suffering poorly.
One day I tell myself in going to build a robot, to comfort me, and do not want history repeats.
Unfortunately it didn't happened. I continue working and found love online.
But I believe we need AI, because human are not perfect ,and has emotions get in our way. In the field of stock investment or military.
Mangirdas Adomaitis on Data analytics and data scienceArtificial inteligence, Data scienceSome time ago
Why many data science projects fail? PART III
Collected data usually have serious quality problems.
Data science is by-product of usual business operations. Business operations are often messy. Building new projects on weak foundations is extra hard.
I don’t know shortcuts here. Companies should embrace analytical culture early on in the journey. Strong data foundation will maximise chances to excel in data science.
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Mangirdas Adomaitis on Data analytics and data scienceArtificial inteligence, Data scienceSome time ago
This week Springer released 65 machine learning books all free of charge.
Top of the list is my favourite "Elements of Statistical Learning by Trevor Hastie et al." 💪
Full list here https://towardsdatascience.com/springer-has-released-65-machine-learning-and-data-books-for-free-961f8181f189
Happy learning
Springer has released 65 Machine Learning and Data books for free
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