Whatever business is running in today’s world, they are creating unlimited data that are increasing exponentially. If you want that vast data turned into unprecedented opportunities, it will influence technology that will store data and analyze it from time to time, and then you must follow data scientists. Data scientist finds unique patterns in data and makes an increasingly accurate prediction that will maximize your future business state. Hence following the steps of a data scientist is very important.
Below is the list of 5 famous data scientists in today’s industry and their details and why one should follow their steps.
- Dean Abbott
- Yann can
- Geoffrey Hinton
- Kenneth Cukier
- Geoffrey Hinton
1. Dean Abbott
He is a data scientist at SmartHQ and president of Abbott Analytics (San Diego). He is famous for having intellect in data mining and predictive analysis. He has experience of two decades about
- fraud detection
- risk modeling
- text mining, personality assessment
- survey analysis
- intensive problem solving
- planned giving
- toxicology, and other applications.
Whoever wants to follow his steps should also take the above career fields seriously.
He founded algorithms for use in pattern recognition and commercial data mining, including two networks; polynomial and neural and clustering algorithm along with radial base function. He also convinces data mining software houses, to provide him critiques and assessments for present and future development.
He also conducts seminars, taught data mining tutorials to live audiences like AAAI, DAMA, KDD, and IEEE. He is an expert in explaining data mining courses to audiences like data analysts, analytics novices, statisticians, and business professionals. If you want to enter the industry, then attend these seminars and learn.
One needs to be like him and follow his steps to be a data scientist. He is good at math and statistics; you should also excel in these to enter the data science industry because it helps to predictive models and advanced analytics solutions.
2. Yann can
He is a French-American scientist on the computer. He primarily works in machine learning, robotics of mobile, computer vision, and computational neurosciences. Yann is also a professor at Courant Institute of Mathematical Sciences, which is located in New York, and he is famous for being vice president of Facebook.com.
He has popularly worked on several in-depth learning projects. Yann holds a degree of Ph.D. in computer science from Université Pierre et Marie Curie
Tips to follow about Yann can
- Choose any one from; machine learning, mobile robotics, and computational neurosciences, also computer vision, and make it your career field.
- Study doctorate degree in computer sciences.
3. Geoffrey Hinton
He is also a computer scientist. He is a famous data scientist and famously known for his work in artificial neural networks.
He introduced the word “dark knowledge” to this world. The core purpose of in-depth knowledge was to train large models by actual information and knowledge. We will first train large models; after that, we will extract in-depth knowledge from it.
Most of the information and knowledge are in minimal probabilities that have literally zero influence on the cost function. This results in no influence on training or test performances too. Hence Geoffrey is widely known for his efforts in artificial neural networks.
He completed his study from Edinburgh University in artificial intelligence.
He is a co-inventor of “Backpropagation” he designed neural nets and deep learning algorithms.
Whoever wants to enter the data scientist industry must follow his footsteps by learning more about Deep Learning, artificial intelligence, and neural networks. Mainly he must focus on neural nets. One must also thoroughly go through his research work “how neural nets can be taught to learn without human help or teacher.”
4. Kenneth Cukier
Everyone has heard about “The economist” Kenneth is a data editor there. He edits data and finds usefulness out of it. He makes sure edited data must be error-free, consistent, and coherent. He is a co-author of a popular data science book named “Big Data: A Revolution That Will Transform How We Live, Work, and Think.” He believes big data is definitely better data.
He was a technology editor in the Wall Street Journal.
One who wants to imitate his data scientist career must read his writings and learn more about data scientists.
5. Yoshua Bengio
Yoshua Bengio is a computer scientist he is most noted for his work in two fields; deep learning and artificial neural networks. He also teaches at Université de Montréal (subjects; computer science and operation research). He started his career at the Canadian Institute for Advanced Research, where he was the co-founder of brain projects and machine learning. In October 2016, he co-founded Element AI, an AI incubator. Which was used to turn AI research into a business application?
Then in 2019, he joined “Botler AI,” which was a tech startup in Montréal.
In one of his interviews, he said people should artificial intelligence and machine learning are core fields to go for if in today’s era. He also said to learn more about natural language understanding.
Corinna Cortes
She is famously known as the head of Google Research in New York City. She studied master’s in physics from Copenhagen University. Then, later on, she joined AT&T Labs, then worked 10+ years there as a researcher. She studied Ph.D. in computer sciences from Rochester. Corinna Cortes studied machine learning and artificial intelligence. Except for these two, she also worked in theory, general sciences, and algorithms.
She is a mother of two and hardworking woman.
In one of the seminars, she shares some tips for beginners,
- Get most out of graduation time
- Learn many skills as you want
- Follow experts in Machine learning and Artificial intelligence.
