Data Science and Machine Learning Platforms Statistics


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Data Science And Machine Learning Platforms Statistics 2023: Facts about Data Science And Machine Learning Platforms outlines the context of what’s happening in the tech world.

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Top Data Science And Machine Learning Platforms Statistics 2023

☰ Use “CTRL+F” to quickly find statistics. There are total 15 Data Science And Machine Learning Platforms Statistics on this page 🙂

Data Science And Machine Learning Platforms “Latest” Statistics

  • According to the U.S. Bureau of Labor Statistics, employment in the industry will increase by 27.9% through 2026 as a result of the need for data science capabilities.[1]
  • A recent report by IBM and Burning Glass states that there will be 364K new job openings in data-driven professions by 2020 in the US.[1]
  • According to KD Nuggets, there were 48 instruments with 2% or more of the market in 2018, and among them, 14 had a loss in share while 34 saw a gain.[2]
  • The top 11 tools have the same percentage of market share in 2019 as they had in 2018.[2]
  • RapidMiner kept its share at around 51%, which was a reflection of both a large user base and a successful campaign to motivate its users.[2]
  • The tools that were part of the KD Nuggets poll in 2018 that reached at least 25 voters and had a share increase of 20% or more.[2]
  • The 20th annual KD Nuggets Software Poll had over 1,800 participants, and the average voter chose 6.1 different tools, so voters with just one choice stood out.[2]
  • The inaugural “Netflix Prize” competition was sponsored in 2006 by media services company Netflix to identify a software that could more accurately forecast user preferences and raise the accuracy of its current Cinematch movie recommendation algorithm by at least 10%.[3]
  • Some machine learning solutions make use of data and six learning algorithms, which operate under the premise that previous success is a good predictor of future success.[3]
  • The top Data Science courses are all included in Coursera Plus, an annual subscription that provides access to more than 3,000 courses, Specializations, Professional Certificates, and Guided Projects.[4]
  • In addition to the enormous demand, there is a severe lack of data scientists who are qualified, with 39% of the most demanding data science occupations needing a degree greater than a bachelors.[1]
  • In the case of the MicroMasters, passing the classes and earning a certificate will credit toward 30% of the Rochester Institute of Technology (RIT)’s complete Master of Science in Data Science degree.[5]
  • Apache Hadoop was identified as the second most crucial ability for a data scientist, according to a research by Villanova University, by 49% of data scientists.[6]
  • In 2018, Python surpassed R as the most widely used language for data science, with 66% of data scientists reporting using it daily.[6]
  • The Villanova University analysis on the data analytics skill gap states that 56% of data scientist employment include SQL as a necessity.[6]

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How Useful is Data Science and Machine Learning Platforms

One of the key benefits of using data science and machine learning platforms is the ability to analyze vast amounts of information quickly and efficiently. Traditionally, analyzing data has been a time-consuming and labor-intensive process that relies heavily on human intervention. With the help of these platforms, businesses can automate the data analysis process, freeing up valuable time for employees to focus on more strategic tasks.

In addition to speed, another key advantage of data science and machine learning platforms is their ability to uncover valuable insights that may not be immediately apparent to humans. These platforms use complex algorithms to sift through data and identify patterns, trends, and correlations that can help businesses make more informed decisions. By leveraging this technology, companies can gain a competitive edge in their industry by identifying new opportunities, predicting future trends, and optimizing their operations.

Furthermore, data science and machine learning platforms enable businesses to personalize their offerings to meet the specific needs of their customers. By analyzing customer data, businesses can better understand their preferences, behaviors, and purchasing habits, allowing them to tailor their products and services to meet individual needs. This level of personalization can lead to increased customer satisfaction, loyalty, and ultimately, revenue.

Moreover, the insights generated by data science and machine learning platforms can also help businesses improve their operational efficiency. By identifying areas of inefficiency or waste, companies can streamline their processes, reduce costs, and increase profitability. For example, a retail company could use these platforms to optimize their inventory management, ensuring that they have the right products in stock at the right time to meet customer demand.

Overall, the use of data science and machine learning platforms is transforming the way businesses operate, enabling them to leverage data in ways that were previously unimaginable. While these platforms are not without their challenges, such as data security and privacy concerns, the benefits far outweigh the risks for many organizations.

In conclusion, the rapid advancements in data science and machine learning platforms have made them indispensable tools for businesses in today’s data-driven world. By leveraging these platforms, businesses can gain valuable insights, improve efficiency, personalize their offerings, and ultimately, drive success. As technology continues to evolve, it is clear that data science and machine learning platforms will play a central role in shaping the future of business.

Reference

  1. mit – https://micromasters.mit.edu/ds/
  2. kdnuggets – https://www.kdnuggets.com/2019/05/poll-top-data-science-machine-learning-platforms.html
  3. wikipedia – https://en.wikipedia.org/wiki/Machine_learning
  4. medium – https://medium.com/javarevisited/5-best-mathematics-and-statistics-courses-for-data-science-and-machine-learning-programmers-bf4c4f34e288
  5. learndatasci – https://www.learndatasci.com/best-data-science-online-courses/
  6. techtarget – https://www.techtarget.com/searchenterpriseai/tip/11-data-science-skills-for-machine-learning-and-AI

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