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Tag: machine learning tutorial

  • Machine Learning Basics | What Is Machine Learning? | Introduction To Machine Learning | Simplilearn

    Machine Learning Basics | What Is Machine Learning? | Introduction To Machine Learning | Simplilearn

    This Machine Learning basics video will help you understand what is Machine Learning, what are the types of Machine Learning – supervised, unsupervised & reinforcement learning, how Machine Learning works with simple examples, and will also explain how Machine Learning is being used in various industries. Machine learning is a core sub-area of artificial intelligence; it enables computers to get into a mode of self-learning without being explicitly programmed. When exposed to new data, these computer programs are enabled to learn, grow, change, and develop by themselves. So, put simply, the iterative aspect of machine learning is the ability to adapt to new data independently. This is possible as programs learn from previous computations and use “pattern recognition” to produce reliable results. Machine learning is starting to reshape how we live, and it’s time we understood what it is and why it matters. Now, let us deep dive into this short video and understand the basics of Machine Learning.

    Below topics are explained in this Machine Learning basics video:
    1. What is Machine Learning? ( 00:21 )
    2. Types of Machine Learning ( 02:43 )
    2. What is Supervised Learning? ( 02:53 )
    3. What is Unsupervised Learning? ( 03:46 )
    4. What is Reinforcement Learning? ( 04:37 )
    5. Machine Learning applications ( 06:25 )

    Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1

    Download the Machine Learning Career Guide to explore and step into the exciting world of Machine Learning, and follow the path towards your dream career- https://www.simplilearn.com/machine-learning-career-guide-pdf?utm_campaign=Machine-Learning-Basics-ukzFI9rgwfU&utm_medium=Tutorials&utm_source=youtube

    Watch more videos on Machine Learning: https://www.youtube.com/watch?v=7JhjINPwfYQ&list=PLEiEAq2VkUULYYgj13YHUWmRePqiu8Ddy

    #MachineLearning #MachineLearningAlgorithms #DataScience #SimplilearnMachineLearning #MachineLearningCourse

    About Simplilearn Machine Learning course:
    A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars. This Machine Learning course prepares engineers, data scientists and other professionals with the knowledge and hands-on skills required for certification and job competency in Machine Learning.

    Why learn Machine Learning?
    Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning
    The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.

    What skills will you learn from this Machine Learning course?

    By the end of this Machine Learning course, you will be able to:

    1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
    2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project.
    3. Acquire a thorough knowledge of the mathematical and heuristic aspects of Machine Learning.
    4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
    5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems

    We recommend this Machine Learning training course for the following professionals in particular:
    1. Developers aspiring to be a data scientist or Machine Learning engineer
    2. Information architects who want to gain expertise in Machine Learning algorithms
    3. Analytics professionals who want to work in Machine Learning or artificial intelligence
    4. Graduates looking to build a career in data science and Machine Learning

    Learn more at: https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Machine-Learning-Basics-ukzFI9rgwfU&utm_medium=Tutorials&utm_source=youtube

    For more updates on courses and tips follow us on:
    – Facebook: https://www.facebook.com/Simplilearn
    – Twitter: https://twitter.com/simplilearn
    – LinkedIn: https://www.linkedin.com/company/simplilearn
    – Website: https://www.simplilearn.com

    Get the Android app: http://bit.ly/1WlVo4u
    Get the iOS app: http://apple.co/1HIO5J0

  • Supervised and Unsupervised Learning In Machine Learning | Machine Learning Tutorial | Simplilearn

    Supervised and Unsupervised Learning In Machine Learning | Machine Learning Tutorial | Simplilearn

    This video on “Supervised and Unsupervised Learning” will help you understand what is machine learning, what are the types of Machine learning, what is supervised machine learning, types of supervised machine learning, what is unsupervised learning, types of unsupervised learning and what are the differences between supervised and unsupervised machine learning. In supervised learning, the model learns from a labeled data whereas in unsupervised learning, model trains itself on unlabelled data. Now, let us get started and understand supervised and unsupervised learning and how they are different from each other.

    Below are the topics explained in this supervised and unsupervised learning in Machine Learning Tutorial-
    1. What is Machine Learning
    – Types of Machine Learning
    – Supervised Learning
    – Unsupervised Learning
    2. Supervised Learning
    – Types of Supervised Learning
    3. Unsupervised Learning
    – Types of Unsupervised Learning

    Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1

    Download the Machine Learning Career Guide to explore and step into the exciting world of Machine Learning, and follow the path towards your dream career- https://www.simplilearn.com/machine-learning-career-guide-pdf?utm_campaign=Supervised-and-Unsupervised-Learning-kE5QZ8G_78c&utm_medium=Tutorials&utm_source=youtube

    You can also go through the Slides here: https://goo.gl/Co9mf1

    Watch more videos on Machine Learning: https://www.youtube.com/watch?v=7JhjINPwfYQ&list=PLEiEAq2VkUULYYgj13YHUWmRePqiu8Ddy

    #MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse

    About Simplilearn Machine Learning course:
    A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with the knowledge and hands-on skills required for certification and job competency in Machine Learning.

    Why learn Machine Learning?
    Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning
    The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.

    What skills will you learn from this Machine Learning course?

    By the end of this Machine Learning course, you will be able to:

    1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
    2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project.
    3. Acquire a thorough knowledge of the mathematical and heuristic aspects of Machine Learning.
    4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
    5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems

    We recommend this Machine Learning training course for the following professionals in particular:
    1. Developers aspiring to be a data scientist or Machine Learning engineer
    2. Information architects who want to gain expertise in Machine Learning algorithms
    3. Analytics professionals who want to work in Machine Learning or artificial intelligence
    4. Graduates looking to build a career in data science and Machine Learning

    Learn more at: https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Supervised-and-Unsupervised-Learning-kE5QZ8G_78c&utm_medium=Tutorials&utm_source=youtube

    For more updates on courses and tips follow us on:
    – Facebook: https://www.facebook.com/Simplilearn
    – Twitter: https://twitter.com/simplilearn
    – LinkedIn: https://www.linkedin.com/company/simplilearn
    – Website: https://www.simplilearn.com

    Get the Android app: http://bit.ly/1WlVo4u
    Get the iOS app: http://apple.co/1HIO5J0

  • AI vs Machine Learning vs Deep Learning | Machine Learning Training with Python | Edureka

    AI vs Machine Learning vs Deep Learning | Machine Learning Training with Python | Edureka

    🔥 NIT Warangal Post Graduate Program on AI and Machine Learning: https://www.edureka.co/nitw-ai-ml-pgp
    This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on “AI vs Machine Learning vs Deep Learning” talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial:

    1. AI vs Machine Learning vs Deep Learning
    2. What is Artificial Intelligence?
    3. Example of Artificial Intelligence
    4. What is Machine Learning?
    5. Example of Machine Learning
    6. What is Deep Learning?
    7. Example of Deep Learning
    8. Machine Learning vs Deep Learning

    Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm

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    Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

    Instagram: https://www.instagram.com/edureka_learning
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    LinkedIn: https://www.linkedin.com/company/edureka
    Telegram: https://t.me/edurekaupdates

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    #edureka #AIvsMLvsDL #PythonTutorial #PythonMachineLearning #PythonTraining

    How it Works?
    1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work
    2. We have a 24×7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
    3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate!

    – – – – – – – – – – – – – – – – –

    About the Course

    Edureka’s Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you:

    1. Master the Basic and Advanced Concepts of Python
    2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs
    3. Master the Concepts of Sequences and File operations
    4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python
    5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application
    6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
    7. Master the concepts of MapReduce in Hadoop
    8. Learn to write Complex MapReduce programs
    9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python
    10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics
    11. Master the concepts of Web scraping in Python
    12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience
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    Why learn Python?

    Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
    Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
    Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next “Big Thing” and a must for Professionals in the Data Analytics domain.

    For more information, please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free).

    Customer Review

    Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: “I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the “customer of Edureka!”. Instructors are knowledge… able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring – All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working.”

  • Random Forest Algorithm – Random Forest Explained | Random Forest in Machine Learning | Simplilearn

    Random Forest Algorithm – Random Forest Explained | Random Forest in Machine Learning | Simplilearn

    This Random Forest Algorithm tutorial will explain how Random Forest algorithm works in Machine Learning. By the end of this video, you will be able to understand what is Machine Learning, what is Classification problem, applications of Random Forest, why we need Random Forest, how it works with simple examples and how to implement Random Forest algorithm in Python.

    Below are the topics covered in this Machine Learning tutorial:

    1. What is Machine Learning?
    2. Applications of Random Forest
    3. What is Classification?
    4. Why Random Forest?
    5. Random Forest and Decision Tree
    6. Use case – Iris Flower Analysis

    Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1

    You can also go through the Slides here: https://goo.gl/K8T4tW

    Machine Learning Articles: https://www.simplilearn.com/what-is-artificial-intelligence-and-why-ai-certification-article?utm_campaign=Random-Forest-Tutorial-eM4uJ6XGnSM&utm_medium=Tutorials&utm_source=youtube

    To gain in-depth knowledge of Machine Learning, check our Machine Learning certification training course: https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Random-Forest-Tutorial-eM4uJ6XGnSM&utm_medium=Tutorials&utm_source=youtube

    #MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse

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    About Simplilearn Machine Learning course:

    A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.This Machine Learning course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in Machine Learning.

    – – – – – – –

    Why learn Machine Learning?

    Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning
    The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.

    – – – – – –

    What skills will you learn from this Machine Learning course?

    By the end of this Machine Learning course, you will be able to:

    1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
    2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project.
    3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning.
    4. Understand the concepts and operation of support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
    5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems

    – – – – – – –

    Who should take this Machine Learning Training Course?

    We recommend this Machine Learning training course for the following professionals in particular:

    1. Developers aspiring to be a data scientist or Machine Learning engineer
    2. Information architects who want to gain expertise in Machine Learning algorithms
    3. Analytics professionals who want to work in Machine Learning or artificial intelligence
    4. Graduates looking to build a career in data science and Machine Learning

    – – – – – –

    For more updates on courses and tips follow us on:
    – Facebook: https://www.facebook.com/Simplilearn
    – Twitter: https://twitter.com/simplilearn
    – LinkedIn: https://www.linkedin.com/company/simplilearn
    – Website: https://www.simplilearn.com

    Get the Android app: http://bit.ly/1WlVo4u
    Get the iOS app: http://apple.co/1HIO5J0

  • Machine Learning Tutorial | Machine Learning Basics | Machine Learning Algorithms | Simplilearn

    Machine Learning Tutorial | Machine Learning Basics | Machine Learning Algorithms | Simplilearn

    This Machine Learning tutorial video is ideal for beginners to learn Machine Learning from scratch. By the end of this tutorial video, you will learn why Machine Learning is so important in our lives, what is Machine Learning, the various types of Machine Learning (Supervised, Unsupervised and Reinforcement learning), how do we choose the right Machine Learning solution, what are the different Machine Learning algorithms and how do they work (with simple examples and use-cases) and finally implement a Machine Learning project/ hands-on demo on Linear Regression Algorithm using Python.

    This Machine Learning tutorial will cover the following topics:

    1. Life without Machine Learning ( 01:06 )
    2. Life with Machine Learning ( 02:29 )
    3. What is Machine Learning ( 04:35 )
    4. Machine Learning Process ( 05:27 )
    5. Types of Machine Learning ( 06:14 )
    6. Supervised Vs Unsupervised ( 09:32 )
    7. The right Machine Learning solutions ( 10:35 )
    8. Machine Learning Algorithms ( 13:33 )
    9. Use case – Predicting the price of a house using Linear Regression ( 23:24 )

    What is Machine Learning: Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.

    Subscribe to our channel for more Machine Learning tutorial videos: https://www.youtube.com/user/Simplilearn?sub_confirmation=1

    Download the Machine Learning Career Guide to explore and step into the exciting world of Machine Learning, and follow the path towards your dream career- https://www.simplilearn.com/machine-learning-career-guide-pdf?utm_campaign=Machine-Learning-Tutorial-G7fPB4OHkys&utm_medium=Tutorials&utm_source=youtube

    You can also go through the Slides here: https://goo.gl/aNmKbQ

    Machine Learning Articles: https://www.simplilearn.com/what-is-artificial-intelligence-and-why-ai-certification-article?utm_campaign=Machine-Learning-Tutorial-G7fPB4OHkys&utm_medium=Tutorials&utm_source=youtube

    We’ve partnered with Purdue University and collaborated with IBM to offer you the unique Post Graduate Program in AI and Machine Learning. Learn more about it here – https://www.simplilearn.com/ai-and-machine-learning-post-graduate-certificate-program-purdue?utm_campaign=Machine-Learning-Tutorial-G7fPB4OHkys&utm_medium=Tutorials&utm_source=youtube

    To gain in-depth knowledge of Machine Learning, check our Machine Learning certification training course: https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Machine-Learning-Tutorial-G7fPB4OHkys&utm_medium=Tutorials&utm_source=youtube

    #MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse

    – – – – – – – –

    About Simplilearn Machine Learning course:

    A form of artificial intelligence, Machine Learning is revolutionizing the world of computing as well as all people’s digital interactions. Machine Learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.

    – – – – – – –

    Why learn Machine Learning?
    Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning
    The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.

    – – – – – –

    What skills will you learn from this Machine Learning course?

    By the end of this Machine Learning course, you will be able to:
    1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
    2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project.
    3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning.

    – – – – – – –

    Who should take this Machine Learning Training Course?

    We recommend this Machine Learning training course for the following professionals in particular:
    1. Developers aspiring to be a data scientist or Machine Learning engineer
    2. Information architects who want to gain expertise in Machine Learning algorithms
    3. Analytics professionals who want to work in Machine Learning or artificial intelligence
    4. Graduates looking to build a career in data science and Machine Learning

    – – – – – –

    For more updates on courses and tips follow us on:
    – Facebook: https://www.facebook.com/Simplilearn
    – Twitter: https://twitter.com/simplilearn
    – LinkedIn: https://www.linkedin.com/company/simplilearn
    – Website: https://www.simplilearn.com

    Get the Android app: http://bit.ly/1WlVo4u
    Get the iOS app: http://apple.co/1HIO5J0

  • What is Artificial Intelligence (or Machine Learning)?

    What is Artificial Intelligence (or Machine Learning)?

    Want to learn more about AI and machine learning? Take this free HubSpot Academy course: https://bit.ly/2Sm2rzG

    What is AI? What is machine learning and how does it work? You’ve probably heard the buzz. The age of artificial intelligence has arrived. But that doesn’t mean it’s easy to wrap your mind around. For the full story on the rise of artificial intelligence, check out The Robot Revolution: http://hubs.ly/H0630650

    Let’s break down the basics of artificial intelligence, bots, and machine learning. Besides, there’s nothing that will impact marketing more in the next five to ten years than artificial intelligence. Learn what the coming revolution means for your day-to-day work, your business, and ultimately, your customers.

    Every day, a large portion of the population is at the mercy of a rising technology, yet few actually understand what it is.

    Artificial intelligence. You know, HAL 9000 and Marvin the Paranoid Android?

    Thanks to books and movies, each generation has formed its own fantasy of a world ruled — or at least served — by robots. We’ve been conditioned to expect flying cars that steer clear of traffic and robotic maids whipping up our weekday dinner.

    But if the age of AI is here, why don’t our lives look more like the Jetsons?

    Well, for starters, that’s a cartoon. And really, if you’ve ever browsed Netflix movie suggestions or told Alexa to order a pizza, you’re probably interacting with artificial intelligence more than you realize.

    And that’s kind of the point. AI is designed so you don’t realize there’s a computer calling the shots. But that also makes understanding what AI is — and what it’s not — a little complicated.

    In basic terms, AI is a broad area of computer science that makes machines seem like they have human intelligence.

    So it’s not only programming a computer to drive a car by obeying traffic signals, but it’s when that program also learns to exhibit signs of human-like road rage.

    As intimidating as it may seem, this technology isn’t new. Actually, for the past half-a-century, it’s been an idea ahead of its time.

    The term “artificial intelligence” was first coined back in 1956 by Dartmouth professor John McCarthy. He called together a group of computer scientists and mathematicians to see if machines could learn like a young child does, using trial and error to develop formal reasoning. The project proposal says they’ll figure out how to make machines “use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.”

    That was more than 60 years ago.

    Since then, AI has remained for the most part in university classrooms and super secret labs … But that’s changing.

    Like all exponential curves, it’s hard to tell when a line that’s slowly ticking upwards is going to skyrocket.

    But during the past few years, a couple of factors have led to AI becoming the next “big” thing: First, huge amounts of data are being created every minute. In fact, 90% of the world’s data has been generated in the past two years. And now thanks to advances in processing speeds, computers can actually make sense of all this information more quickly. Because of this, tech giants and venture capitalists have bought into AI and are infusing the market with cash and new applications.

    Very soon, AI will become a little less artificial, and a lot more intelligent.

    Now the question is: Should you brace yourself for yet another Terminator movie, live on your city streets?

    Not exactly. In fact, stop thinking of robots. When it comes to AI, a robot is nothing more than the shell concealing what’s actually used to power the technology.

    That means AI can manifest itself in many different ways. Let’s break down the options…

    First, you have your bots. They’re text-based and incredibly powerful, but they have limitations.

    Ask a weather bot for the forecast, and it will tell you it’s partly cloudy with a high of 57. But ask that same bot what time it is in Tokyo, and it’ll get a little confused. That’s because the bot’s creator only programmed it to give you the weather by pulling from a specific data source.

    Natural language processing makes these bots a bit more sophisticated. When you ask Siri or Cortana where the closest gas station is, it’s really just translating your voice into text, feeding it to a search engine, and reading the answer back in human syntax. So in other words, you don’t have to speak in code.

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    Want to stay current on emerging tech? Check out our free guide today: http://bit.ly/2GJesc2