Machine Learning Tutorial Part – 1 | Machine Learning Tutorial For Beginners Part – 1 | Simplilearn




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This Machine Learning tutorial will help you understand why Machine Learning came into picture, what is Machine Learning, types of Machine Learning, Machine Learning algorithms with a detailed explanation on linear regression, decision tree & support vector machine and at the end you will also see a use case implementation where we classify whether a recipe is of a cupcake or muffin using SVM algorithm. 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, to put simply, the iterative aspect of machine learning is the ability to adapt to new data independently. Now, let us get started with this Machine Learning tutorial video and understand what it is and why it matters.

Machine Learning Tutorial Part – 2: https://www.youtube.com/watch?v=_Wkx_447zBM

Below topics are explained in this Machine Learning tutorial:
1. Why Machine Learning? ( 00:45 )
2. What is Machine Learning? ( 04:52 )
3. Types of Machine Learning ( 11:34 )
4. Machine Learning Algorithms ( 16:41 )
– Linear Regression ( 16:57 )
– Decision Trees ( 25:43 )
– Support Vector Machine ( 34:00 )
5. Use case: Classify whether a recipe is of a cupcake or a muffin using SVM ( 36:02 )

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://bit.ly/2VTB8Nc

You can also go through the Slides here: https://goo.gl/m5Txob

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

#MachineLearning #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.

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-Tutorial-DWsJc1xnOZo&utm_medium=Tutorials&utm_source=youtube

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Comment List

  • Simplilearn
    November 19, 2020

    Machine Learning is the Future and yours can begin today. Comment below with your email to get our latest Machine Learning Career Guide. Let your journey begin.

    Do you have any questions on this topic? Please share your feedback in the comment section below and we'll have our experts answer it for you.
    Do not forget to attempt the quiz (10:00). We will give out the answers to the quiz in Machine Learning Tutorial Part – 2 video. Stay tuned!

  • Simplilearn
    November 19, 2020

    Hi love the tutorial could you provide me with the data sets (study material) ? My email is sayedsaquib88@gmail.com

  • Simplilearn
    November 19, 2020

    Hello Simplilearn,
    just loved your tutorial.
    Can you please send the datasets that you have used, to the email id praveenjakhar181@gmail.com

  • Simplilearn
    November 19, 2020

    Hello Simplilearn team, this is a great video. Could you please send me the study material , datasets and codes used in this tutorial.

  • Simplilearn
    November 19, 2020

    Great video…thank you so much. Please can I also have the dataset. my email is bisi.bf@gmail.com

  • Simplilearn
    November 19, 2020

    Hello, thank you for taking your time to put this out, can I please get the datasets used in this tutorial, email address is eetari@ymail.com . Thank you.

  • Simplilearn
    November 19, 2020

    A great
    tutorial indeed! Could you please send me the study material , datasets and source codes used in this tutorial ??

    My Email ID : honeywas34@gmail.com

  • Simplilearn
    November 19, 2020

    ould you send me the dataset plzzzzz? My email is p.supraja18@gmail.com

  • Simplilearn
    November 19, 2020

    I know this is a year later but when i type:: model = svm.SVC(kernel = 'linear') model.fit(ingredients, type_label) the output i get is SVC(kernel='linear') and that's it.

  • Simplilearn
    November 19, 2020

    5:15 Not my cell phone. It can barely run Google Maps.

  • Simplilearn
    November 19, 2020

    This is very interesting. I was thinking it was a lot harder, but it's not. It is hard but easier than I thought.

  • Simplilearn
    November 19, 2020

    I really like the 666k subscribers. This made me subscribe too.

  • Simplilearn
    November 19, 2020

    Hi I loved your tutorial. Can I please have a copy of the dataset at "mikalkimmani@gmail.com"

  • Simplilearn
    November 19, 2020

    could I get the data as well? thatisreallycoolnot@gmail.com

  • Simplilearn
    November 19, 2020

    very bad sound quality

  • Simplilearn
    November 19, 2020

    great work
    please sends me dataset at bilal.shabir528@gmail.com

  • Simplilearn
    November 19, 2020

    Hello! Love the tutorial. Could you provide me with the data sets? My email is alexsusia@hotmail.com

  • Simplilearn
    November 19, 2020

    That microphone is pure shite

  • Simplilearn
    November 19, 2020

    Awesome tutorial!!! Explained very well for a beginner.

  • Simplilearn
    November 19, 2020

    Thanks a lot for this

  • Simplilearn
    November 19, 2020

    At 30:16 shouldn't it be E(9,5) since the 9 is yes and the 5 is no?

  • Simplilearn
    November 19, 2020

    I think I’ve found right place to learn Machine Learning. I request you to send essential materials to my email
    3420karthik@gmail.com

    Thank you in advance😇

  • Simplilearn
    November 19, 2020

    Hii I loved your tutorial
    Can you please send me the materials and codes on my Email
    anushkatiwari2108@gmail.com

  • Simplilearn
    November 19, 2020

    Great content. Have subscribed to your channel. Please forward me the datasets and other related material used in this course. email: sahniarjun0105@gmail.com. Thanks!

  • Simplilearn
    November 19, 2020

    I got an error after typing this
    model = svm.SVC(kernel='linear')

    model.fit(ingredients, type_label)
    ValueError: The number of classes has to be greater than one; got 1 class
    what to do?

  • Simplilearn
    November 19, 2020

    Will check your formulas for the entropy, but what really threw me off was that you said "log squared", whereas it was just log with the base of 2. Also, in your subsequent calculations, p + n equals 1, which would have greatly simplified the formula if you knew what you were talking about. And I went like uh-oh, this guy doesn't even know the formula he's using. Your explanation is just horrible. Instead of reading out loud all the numbers, confusing plus and multiplication for equals sign, you should have explained what the formula means and why is it like it is. That topic was a complete screw up. Typical American skateboarder style programmer. Wish you had proper education. I'm stopping watching this video right here and not recommending anyone. Go ride your skateboard man, "you know what I'm talkin' 'bout?"

  • Simplilearn
    November 19, 2020

    please now starting machine learning. can i get the datasets? (patrickackom003@gmail.com)

  • Simplilearn
    November 19, 2020

    A great
    tutorial indeed! Could you please send me the study material , datasets and source codes used in this tutorial ??
    My Email ID : panditrk2000@gmail.com

  • Simplilearn
    November 19, 2020

    will you please send me the data sets and other materials of the video to emonchy209@gamil.com ?

  • Simplilearn
    November 19, 2020

    A – Classification, B- Clustering, C – Anomaly Detection, D- Regression

  • Simplilearn
    November 19, 2020

    can i get the dataset please? ainnazafar@gmail.com

  • Simplilearn
    November 19, 2020

    at 31:10, why is it the I(3,2) and I(4,0) and I(2,3) ? Shouldn't it be I(3/5,2/5) and I( 4/4, 0/4) and I ( 2/5, 3/5) ?

  • Simplilearn
    November 19, 2020

    For the record at 17:27 c is your Y-intercept and m is your coefficient (or better known as the slope). Set x to 0 and you are left with y = c. At 29:44 it's not Log squared. It's Log Base 2. Log without the subscript is Log Base 10. It's also not Log "root 2".

  • Simplilearn
    November 19, 2020

    To those who have no idea what Go is: It's like chess but bloody more difficult.

  • Simplilearn
    November 19, 2020

    sir can i get datasets used in this video my mail id is s1998abraham@gmail.com

  • Simplilearn
    November 19, 2020

    Thanks so much for this informative video. Kindly send me the datasets. My email is darelasisi@gmail.com.

  • Simplilearn
    November 19, 2020

    Hello…darelasisi@gmail.com, I wish to know more about ML. I am currently researching on ML. Thanks.

  • Simplilearn
    November 19, 2020

    Could you please send me the data set used in this tutorial to arbi.oussama@gmail.com

  • Simplilearn
    November 19, 2020

    I made the data set from scratch and it worked just pause the video when he shows the file. Type it in excel and save as CSV, then make sure you upload it to Jupiter notebook. It will work

  • Simplilearn
    November 19, 2020

    Done with subscription, I would like you send me the dateset used in this course, please, here is my email: mjados@outlook.com, thanks!

  • Simplilearn
    November 19, 2020

    Hello Simplilearn. I loved watching this tutorial! Please share the dataset with me, my email is lazySnacker95@gmail.com. Thank you!

  • Simplilearn
    November 19, 2020

    This is a great
    tutorial! Could you please send me the study material , datasets and codes used in this tutorial ??
    My Email ID :
    02pkurle@gmail.com

  • Simplilearn
    November 19, 2020

    I have no idea what im doing here, never finished college, failed all my math classes, no idea how to code…..but this thing intrigues me

  • Simplilearn
    November 19, 2020

    Thanks for this amazing video. Could you please send me the datasets? My email donaldo24ever@gmail.com thanks.

  • Simplilearn
    November 19, 2020

    Very good tutorial 🙌🙌 .Can you please send me a copy of dataset here at deepakparihar223@gmail.com

  • Simplilearn
    November 19, 2020

    Hi, Can I have the data sets sent to mashikoo@gmail.com, please?

  • Simplilearn
    November 19, 2020

    Nice vedio. Can you give me an access to the dataset. My email Id=mehnaazyeasmim786@gmail.com

  • Simplilearn
    November 19, 2020

    thank you

  • Simplilearn
    November 19, 2020

    Thank you for this course. You can send me the file of the dataset

  • Simplilearn
    November 19, 2020

    Kindly send me the dataset to kimhoox@gmail.com

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