Introduction
Data can't improve your past. But nevertheless, can surely create amazing future.
In recent years, companies have invested millions of dollars in the field of data science. They have shown immense faith in their potential to create a better world, a better life and a better future.
The mighty math trio, IT and domain expertise has redefined the decision-making process. Intuition or instinct is no longer the key to making difficult decisions.
What was considered a pioneering invention a few years ago, now it has become obsolete. Data science has given us possibilities beyond imagination. Over the years, many things have deteriorated and evolved. Even so, the best of technology is yet to come. I am excited to see it in front of my eyes!
What do these pictures show?
We all know that images are easy to understand and convey more information than text.. Basically, these images represent the data science journey as a field. These include developments, inventions, achievements and everything that has had an impact on our daily lives.
You talk about politics, economy, science, life, sports, almost everything is blessed by data science services. And I have tried to capture the best of them in these images.
I hope you like them!
20 photos
1. This event marked the beginning of the 'data scientists' revolution.. After this research report was published, the world immediately recognized the “potential” necessary to make sense of the data.
2. Mckinsey further fueled this revolution with his research report on the growing imbalance in the demand and supply of talent with analytical talent.. But nevertheless, this focused only on the US market, but its repercussions were felt in industries around the world. (Image source: Informe McKinsey)
3. This was the first advance in Artificial Intelligence. IBM created its first computer with artificial intelligence IBM Watson. It was created to compete on the popular game show ‘Jeopardy’. Finally, Watson defeated two of these great Jeopardy champions (Ken and brad). This ushered in next-level artificial intelligence..
4. Data science plays an important role in baseball. This caused a sudden increase in the demand and availability of player data close to 2000. It is said that the years after 2000 marked the beginning of data revolution in baseball. (Image source: Datanami)
5. In 2009, Netflix ran a contest to improve the accuracy and relevance of your recommended content system. This team solved the mystery. Won a cash prize of $ 1,000,000. Undoubtedly, this is one of the most remarkable events in the history of data science.
6. This is the best stat. Peter Brand (Moneyball) statistically explains the numbers game that can give you wins in the upcoming baseball season. His popular dialogue “In baseball, the goal should not be to buy players. The goal should be to buy wins. To buy prizes, you need to buy races! “
7. In the presidential elections of 2012, Nate Silver predicted correctly 50 of 50 state. Used probability, Graphic Schema Theory, Bayes theorem techniques to accomplish this feat. This level of precision brought about by the use of statistics completely changed the way of making political predictions..
8. Will this be the decade of Deep learning ? This image shows the number of deep learning projects carried out by Google in the last 4 years. (Image source: Bloomberg)
9. It's a competition between Google's image recognition software and a Soduku champion. (human). While the champion does her analysis and finds the correct numbers, google glasses solves it in seconds.
10. Industrial robots in action in a car factory. These robots provide high precision, low margin of error and faster response rate than humans. The automotive manufacturing industry is moving towards this automated way of working.
11. Burn stress. Yes! Stress can also be recorded in the form of data. Now, there are several devices and applications available in the market that can record the level of stress and predict probable health problems.
12. We talk about new data collection methods, here's another. Companies have created applications and software to track your fitness levels and recommend health products accordingly. Everything you do today generates data.
13. Easier expedition. This Image recognition the software translates the text instantly. You no longer need to face unfamiliar language problems traveling to a new country.
14. In 2012, other groundbreaking research was produced in the field of data science. And Google, a computer learned to identify cats using a Red neuronal created using 16.000 computer processors.
15. Unmanned aerial vehicle (UAV), also know as Drones they are airplanes that are pre-programmed for a certain mission. It can be security (spy cam), delivery of goods, monitoring, etc. It is an advanced way of producing data that was previously considered difficult to capture.
sixteen. Self-driving cars. Google research, Baidu, Ford are working diligently on this project. This is a perfect example of a machine that learns from its environment. ¿Ves, this car detects a person crossing the street?
17. Every moment, artificial intelligence it's getting better to defy human intuition. Robots can now look and think like humans. But nevertheless, ESP remains a challenge. Do not be disappointed if you see many of these species in our environment in the near future..
18. Internet of Things promises an incredible future for humans. Creating a network of connected devices will make human life faster and more comfortable. (Image source: The Connectivist)
19. Machine learning will now promote life. Google continues to inspire humans with its projects. This is the Google Verily project. His goal is to make robots better surgical assistants through machine learning and advanced image processing.. (Image source: Verily)
20. Google Trends also shows promising data science growth in 2016.
Final notes
This article is about 20 images showing the remarkable growth of data science and machine learning. Nobody wondered if the combination of data and technology could design a fantastic future. But nevertheless, this decade will experience this future.
One thing I learned while compiling this article is that if anyone wants to get into data science and analytics, can't wait for a better time. That's it. Do it now. Companies are furiously looking for talented candidates. Be the first.
