Wolfram Research, Inc., creator of Mathematica, Wolfram|Alpha and the Wolfram Language, announces the integration of Wolfram technology with SolveBio, the operating system for precision medicine that enables biotech and pharmaceutical companies to leverage molecular information for therapeutic development.
Source: PR Newswire
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Scientists crunching numbers on infant deaths in the US are using data-analysis algorithms to try and find new ways to reduce the number of babies lost to SIDS each year, with Microsoft contributing free cloud hosting and software tools for their work.
Source: The Star5604
Data science is the theory and practice powering the data-driven transformations we are seeing across industry and society today. Artificial intelligence (AI), self-driving cars, and predictive analytics are just a few of the breakthroughs that have been made thanks to our ever-growing ability to collect and analyze data.
Source: Data Informed12351
Want to be a data scientist? Third-level institutions and full-time education aren't the only way you can learn essential data science skills.
Source: Siliconrepublic10698
Well-established enterprises like retailers or manufacturing companies now have an abundance of data at their disposal. Unfortunately, merely possessing vast amounts of raw data does not lead directly to increased efficiency or the rapid development of new revenue streams. Instead, everyone must now figure out exactly how to make this data work for them.
Source: Computerweekly13068
The words artificial intelligence often conjure up a sense of fear and apprehension. Fear for the unknown possibilities of AI, fear for the AI-fueled dystopian images brought about by movies like The Terminator, and most practically, fear for the possibility that AI will someday take our jobs.
Source: VB15060
Does it seem like the ability to find, hire and retain data scientists is a losing battle? Is spending $500.000-plus per year for a data scientist worth it? What is a data scientist anyway?
Source: IM10515
Coupled with technology, data can transform the way businesses operate to stay ahead of their competitors.
Source: Daily Nation5676
While all the attention is on the data scientists, it's market research where the really interesting work is says Ryan Howard.
Source: RESEARCHLIVE6792
Machine learning engineers, data scientists, and Big Data engineers are among the top emerging jobs in technology. This is based off of a recently released report from LinkedIn.
Source: SD Times7518
Special thanks to Michael Shepherd, AI Research Strategist, Dell EMC Services, for his co-authorship. Learn more about Michael at the bottom of this post.
Source: Linkedin Pulse13827
Based on historical data and accurately predicting some patterns out of it then, Data science comes into the picture. Data Science is the data driven decision making and building business strategies based on data analysis by removing any manual or judgemental error. Data Science is everywhere and here is the rescue for how to be a data scientist.
Source: HOB6369
Leveraging the application of big data, whether it is to improve the process of product development, improve customer retention or work through the data to find new business possibilities organizations are more relying on the expertise of data scientists to sustain, grow and beat their competition. Consequently, as the market for data scientists increases, the system presents an exciting career path for students and existing professional.
Source: HOB19524
According to an IDC Digital Universe Study, by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet. Uncovering insights from this homogenous amount of information will require the seamless adoption of big data technologies, stronger data security, and integration of AI, machine learning and cognitive technologies applications with business operations
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The exploding demand for data scientists is representative of a need that will not slow down anytime soon. The monetary value of storing, workings with and drawing penetration from data keeps falling the demand for professionals that can work with this data and deliver on the insight will continue to grow.
Source: HOB11973
Data science is ubiquitous and is broadening its branches all over the world. The invisible hand of data science in the form of ranking algorithm governs the news streams and feed, recommendation engines that guide the content we see on Netflix and YouTube. Similarly, survival analyses for the estimation of time queues and neural networks for self-driving cars. But there includes a lot of challenges which hinders a data scientist while dealing with data.
Source: HOB5361
Artificial intelligence is the future. Google, Microsoft, Amazon and Apple are all making big bets on AI. Artificial Intelligence (AI) is all the rage from self-driving cars and Siri personal assistants, to chatbots and email scheduling agents that will take routine tasks out of human hands.
Source: HOB5751
Numbers don't lie, data analytics is on rise soon it will be integrate part of all the organizations. Data science has created so much hype in the world of IT sectors that from big to small companies all are now hiring employees who have knowledge regarding this subject. Data science helps an employee to understand data and then synthesize it in a proper way so that they can communicate in a better way which is beneficial for the companies
Source: HOB4713
Data science informs entrepreneurs in a way that listening to their gut just can't.
Source: HOB9267
Harvard hosts some of the most prestigious programs in the world, especially in business and law. So it was big news in the data science industry when the university announced a new master's program in data science in March 2017
Source: HOB9933
Based on historical data and accurately predicting some patterns out of it then, Data science comes into the picture. Data Science is the data driven decision making and building business strategies based on data analysis by removing any manual or judgmental error. Data Science is everywhere and here is the rescue for how to be a data scientist. Data scientists basically deal with huge no of both the data whether structured or not structured and the future of data scientists will be data psychology.
Source: HOB4122
Data science has created so much hype in the world of IT sectors that from big to small companies all are now hiring employees who have knowledge regarding this subject. Data science is helpful for the employees to get understand about data and then make it in a proper way so that it can be communicated in a better way which is valuable for the companies.
Source: HOB9768
Leveraging the application of big data, whether it is to improve the process of product development, improve customer retention or work through the data to find new business possibilities organizations are more relying on the expertise of data scientists to sustain, grow and beat their competition. Consequently, as the market for data scientists increases, the system presents an exciting career path for students and existing professional.
Source: HOB4068
Analytic is the interpretation of the data collected. Raw form of data is not of any use. It is important to convert raw data into analytic so that it is easier to find that what is the decision that are to be taken by the use of analytic. Businesses use this analytic for making actionable business analytic that will help them in taking real time actions.
Source: HOB11895
Apache Spark is an open-source cluster computing framework for real-time processing. It has a thriving open-source community and is the most active Apache project at the moment. Spark provides an interface for programming entire clusters with implicit data parallelism and fault-tolerance.
Source: HOB6801
For any tech enthusiast, knowing certain Machine Learning Algorithms and its applications have now become very important. Tech giants like Google, Amazon, Facebook, Walmart are using Machine Learning significantly to keep their business tight enough to compete with their rivalries.
Source: HOB4509
Data Scientists are big data wranglers. They consider mass and messy data both structured and unstructured and use their formidable skills and organize them accordingly. They use or apply their analytics power to uncover hidden solutions to business challenges.
Source: HOB9729
It was declared as the "sexiest job of the 21st century," by Harvard Business Review. While the job has got a great description by Harvard the career path for now is a bit uncertain.
Source: HOB7554
Data Scientists is the highest paying and demanding job in the current year. All HR professionals are under pressure to get hired the best data science talent so they can achieve the valuable business insights. According to Harvard Business Review described the role of data scientists as it is the sexiest job of the 21st century.
Source: HOB2946
Big Data Analytics is the perfect solution for the complex problems. Every marketer have to take right decision for their organization and now for all those decisions they need not to be depend on their employees. With the help of big data analytics they can easily come to know about each fact and findings.
Source: HOB4173
With data sciences being the focal point, Entrepreneur India analyses why this new trend is now the essential tool for a majority of smart entrepreneurial solutions.
Source: HOB5169
The growth of data and its usage across the industry is hidden from none. During the last decade in general, and the last couple of years in particular, we have seen a major distinction in the roles tasked with crafting and managing data.
Source: HOB4680
In today's world with the introduction of "Internet of Things" and the improvement of "AI Technology" has led to implementation of big data solutions to almost every organization whether small or large organizations. With the help of big data analytics the management can easily take the decision and improve their operational efficiency.
Source: HOB5121
Around Data Science Platforms all of its functionalities like data exploration and integration from several sources, coding, model building are executed. Data science platforms are programmed to train and test models and deploy the results to solve real-life business challenges.
Source: HOB7359
Now a day's most of the organizations are using Data Science capabilities to shape the next set of products which will be more personalized and dynamic. Businesses across verticals have been sitting on huge quantities of data over the years, in various forms like customer, partner, and internal data.
Source: HOB6486
Machine learning is increasingly being deployed in credit card purchase fraud detection, personalized advertising though pattern identification, personalized shopping/entertainment recommendations, to determine cab arrival times, pick-up locations, and finding routes on maps.
Source: HOB4161
Data scientists who find themselves straying too far away from technical work may quickly find their skills out of date and unmarketable in today's climate.
Source: HOB3816
The data scientist role is fast becoming the most sought after career of the technology world. We asked top data scientist Jake Porway from The New York Times about how he got his job and his tips for success in the field.
Source: HOB5460
The data scientist role is fast becoming the most sought after career of the technology world. We asked top data scientist Jake Porway from The New York Times about how he got his job and his tips for success in the field.
Source: HOB2391
Data Scientists are leaving their jobs, And according to Financial Times it's correct that data scientists usually spend 1-2 hours a week to find good opportunities. We read so many stories about data science being the sexiest job of the 21st century and the attractive sums of money that you can make as a data scientist that it can seem like the absolute dream job.
Source: HOB7125
With the manifold of data science tools in the market, it is certainly a rising challenge for you as a data scientist or a blooming data scientist to sort out the best ones.
Source: HOB7920
Yet the task description of data scientists is ever-changing. the increase of computing, machine learning, and automatic information assortment means that the character of their work is shifting at a speedy pace. Time-intensive tasks, together with information assortment, have become less primary as they become machine-driven, giving thanks to additional strategic tasks.
Source: HOB4647
Over the past years, it was witnessed that data science is majorly used by everyone and there are rise and fall of some words like big data, business intelligence, analytics and these days artificial intelligence. Today there are many aspiring data scientists who are encouraged in learning the techniques of modeling. There are several books which will help a data scientist to get prepared philosophically.
Source: HOB26226
Across many industries, there are many large enterprises and businesses having the high performance which are tidily turning towards artificial intelligence and new analytics to make the decisions faster, productively and data-driven.
Source: HOB3474
Four forces are deep at work altering the landscape for marketing in 2019 and beyond. The forces and the opportunities they represent are hidden in plain sight. Take privacy for example. Many still view privacy policies as a check-the-box legal exercise, yet consumer attitudes toward privacy and data collection have fundamentally changed.
Source: HOB3327
Across many industries, big data is being used to drive decisions which are informed and better ones. But it is used in the legal industry is relatively new, mainly because most law firms are resistant to both change and new IT expenditures on unfamiliar initiatives.
Source: HOB3024
Machine Learning is the most powerful tool that businesses are using today. Software and machines have been developed which are not just performing operations for businesses but also enhancing and reshaping the business.
Source: HOB5361
Here are two courses by famous writers which will help you in building your skills in deep learning and artificial intelligence.
Source: HOB2958
There are multiple reasons why your analytics strategy might not be working. Here is the overview of why is it so and how you can overcome them.
Source: HOB4767
When we talk about machine learning, the eye of the media is a blessing as well as the curse. Although it's great that AI has captivated the general public, the way that the media discusses it often obscures the meaning of the term entirely.
Source: HOB3777
Google's machine learning program launched 11 Feb 2019 at Mills College in Oakland, California, and will train a cohort of future data scientists to help address the country's computer science workforce gap.
Source: HOB10455
There is too much explosion in the generation of the data in every major industry all around the world, and the demand of skilled workers if very much as they need professional workers to handle that huge data for solving certain problems and this profession has an unpredictable growth in recent times.
Source: HOB2613
It seems that these days building a career is a bit dicey task and here you will see how to build a career in machine learning with R programming language.
Source: HOB2319
In regards to bitcoin, blockchains implications to data science are quite transparent.
Source: HOB2529
This article is supposed to make you familiar you some of the most useful books on Computer Vision which will give you a thorough understanding of the field and will imbibe deeper understanding in you of the various concepts.
Source: HOB2316
Statistics plays a very important role in Data Science. The article draws out some statistical concepts that every Data Scientist should know.
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This article will dive through some of the most Frequently Asked questions in Data Science Interviews with the help of a popular video of YouTube so that your preparation for the next Data Science interview becomes easier.
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The report by Gartner states Augmented Analytics as an approach that automates insights using machine learning and natural language generation.
Source: HOB5775
The 7 most important terms in Data Science that every Data Scientist must know while making a career in Data Science are discussed in the present article.
Source: HOB3366
This article discusses those top 3 skills which are required by every Data scientist and it won't be wrong to say that these 3 skills are like the 3 keys in unlocking your success-door in the field. It thus becomes very important that you take these 3 skills very sincerely and start developing them right from today.
Source: HOB2589
Data is everywhere. Data is flooding. Data is in huge quantity. But how do I find insights out of this data? This is the big question which everyone asks in this data-driven world.
Source: HOB1764
Books are always the best sources to explore while learning a new thing. Reinforcement Learning has finds its huge applications in recent times with categories like Autonomous Driving, Computer Vision, Robotics, Education and many others. Here are some best books on Reinforcement Learning that you can easily find on Amazon
Source: HOB3684
With an Average base salary of $146085, Machine Learning Engineer stood as the best job in the U.S FOR 2019 according to a recent report by Indeed.
Source: HOB3000
Whether you just want to stay informed in the data craze or you're looking to kickstart your data science or data literacy journey, this article features a list of books.
Source: HOB2769
For a beginner who want to start a career in Data Science, a lot of online platforms are available providing a bunch of information about the field and offering several courses but still there is some ambiguity that still lies in the mind of the aspirants about the careers, salaries, growth rate, skills, and the the various positions in Data Science.
Source: HOB3024
Thanks to Machine Learning that businesses can now be reliable to Machine learning in knowing their customers, predicting their customer wants, assisting their customers and moving the business to the next level.
Source: HOB5484
There are a number of online resources that have emerged today to teach learners the various concepts and things related to Data Science that it is a bit confusing to get started with any.
Source: HOB2439
It doesn't matter how much data businesses collect, unless they are unable to find actionable insights out of it, all data collected is useless.
Source: HOB1695
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