What is Machine Learning? | Machine Learning Basics | Machine Learning Tutorial | Edureka
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- Опубликовано: 16 июн 2024
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This Edureka video on "What is Machine Learning" (Machine Learning Blog: goo.gl/fe7ykh ) gives an introduction to Machine Learning and its various types. Below are the topics covered in this tutorial:
1. Evolution of Machine Learning
2. What is Machine Learning?
3. Types of Machine Learning
4. Supervised Learning
5. Unsupervised Learning
6. Reinforcement Learning
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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:
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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.
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Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka Python Machine Learning Course curriculum, Visit our Website: bit.ly/37q65Oc
I'm speechless, the video i was looking for. Do you guys have video on Probability and stats for Data science?
Very very thank you sir, I searched many channels, but edureca is a unique one, such a simple and better explanation, mai aapka ehsaan kabhi nhi bhoolunga, i learnt so much from you😘😘😘
so much useful!☺ Atul
Wow thank you for this . It was very helpful .
Great job sir... Thank you for your videos... And what are the algorithms used in reinforcement ML
Mast he vi. awesome work
It's very clear explanation sir
One of the best channels i refer to.Great work guys.
Hey Priyam, that feels great to know. We are delighted to see learners use our content and learn new technologies. Do subscribe to our channel and stay connected with us. Cheers :)
Great great and great
Good one
Thanks 😆
I just want to take time to appreciate the effort you guys are putting in delivering quality content to the viewers .. I always follow your videos and suggest them to friends as well, and they're very helpful .. Edureka has helped me in shaping my career ..
I hope you continue this effort going forward, and provide more good content ..
Hey Deepika, glad that our channel made you feel this way. We are delighted that our videos helped you understand and achieve your goals. Do continue supporting us and we assure you that we won't disappoint. Cheers!
That was really good... Ty... 😊😊😊
Wow...Such a clear explanation.Thanks.
Thanks for the compliment Nazifa! We are glad you loved the video. Do subscribe to the channel and hit the bell icon to never miss an update from us in the video. Cheers!
your voice is amazing.... well nice tutorial gr8 explanation simple and qualitative one. Thanks
great explanation. it's really helpful for me thanku sir.
You are most welcome Chandana. Don't forget to Subscribe our channel.
Sir you have cleared my confusion differences between ai,ml,dl. And I have another thing to clear with in these three subjects which I would learn
Hi Sarada, It's recommended to go with Machine Learning first and then AI. Deep learning is a separate technology and you can learn it once you are well versed with the first two.
Thank you for an insightful video on machine learning. It's very informative especially for people like me who has no prior knowledge of ML.
I have a question.
Whether the number of clusters in unsupervised learning needs to be predefined ? or does it create new cluster if it finds any of the previous clusters are not suitable ? Is there any limit on number of clusters it can create ?
Hey Roshan, Yes you have to define the number of clusters that you want to create and based on that the unsupervised algorithm will create clusters based on the similarities it finds in the data.
Hope this helps!
@@edurekaIN Thank you very much for clarifying me :-)
Nice explanation with simplistic examples. Bravo👏
Thank You 😊 Glad you liked it!! Keep learning with us..
It was an honour to be here will you please tell me What’s the trade-off between bias and variance? Thankyou so much
Hey Azhar, Bias of an estimator is the difference between this estimator's expected value and the true value of the parameter being estimated. ... The variance of an estimator, on the other hand, does not depend on the parameter being estimated. It is a measure of how far values can the estimate take, away from its expected value. Hope this helps!
Very useful content
Great work keep uploading videos like this
Hey Sana, we strive hard tomake sure that we put out quality content. Do subscribe to us and stay connected with us. Cheers :)
edureka! De ñ
sana khan que
Video was good I got clear information
Thank you for watching our video. Do subscribe, like and share to stay connected with us. Cheers :)
Thank you sir!
Well explanation 🙂
Thank you so much for your review on our channel Great to hear that Edureka is helping you learn better . We’ll strive to make even better learning contents/courses in the future ! Do subscribe the channel for more updates : )
Thanks sir 👍
Edureka is superb
Thank you 😊 Keep learning with us!!
Thank you so much 👍👍great video indeed 🙏👍
Thanks for watching! Glad you liked it ! We are glad to have learners like you . Do subscribe our channel and hit that bell icon to never miss an video from our channel .
Thank you sir.
Ver fast explaining....
You're Welcome 😊 We have taken your suggestion into consideration!! Keep learning with us..
More examples on reinforcement learning..
Your videos content are awesome keep uploading videos like this.
Hey Jayant, thank you for appreciating our work. Do subscribe and stay connected with us. Cheers :)
superb explanation...kudos....
Thank you so much for the review ,we appreciate your efforts : ) We are glad that you have enjoyed your learning experience with us .Thank You for being a part of our Edureka team : ) Do subscribe the channel for more updates : ) Hit the bell icon to never miss an update from our channel : )
sir you have explained very well. thnk you sir
You're Welcome 😊 Glad it was helpful! Keep learning with us..
I think at 11.07 heading of slide should be "Unsupervised Learning Algorithms".
Hey H V, thank you for pointing this out. Cheers :)
Is there any tutorial explaining all this three algorithms on this channel?
Thanks man to make me clear about ml
Hey Aman, glad you loved the video. Do subscribe and hit the bell icon to never miss an update from us in the future. Cheers!
great sir
loved it 💜👍✔💯
Thank you. You can also check out our complete training here:
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you said , in retail domain, system recommend the products to customer based on past purchase so this should comes under supervised learning as we have labeled data or labeld products ...could you please clarify it please?
me too have the same querry
I'm not sure if this is correct but I'll try to answer this question as best as I can.
This cannot be considered as supervised learning because you're not using data in the form of inputs and outputs. You only have one set of data, i.e. the products that you have bought earlier. I guess what the unsupervised learning algorithm does is that whatever items you have bought, it extracts their common features and based on that, makes a recommendation.
one doubt in unsupervised learning, if there is no training data set or past data to train the model, the input data comes in and based on the behavioral characteristics we are clustering, then how come "Recommendation to customers based on past purchase" come under unsupervised learning. Kindly correct me if I am wrong.. What is the difference between this category (Shopping/Retail) example pertaining to supervised and Unsupervised learning? How does it differ?
In unsupervised learning, clusters are formed according to the past behavioral characteristics of customers, which is a part of the training data. Clusters are formed based on purchase details, transaction details etc and then recommendations are shown to customers in the cluster. Recommendation engine is a prime example of unsupervised learning. Hope this helps :)
edureka! Thank you... I understood it now!...
_/\_ Very infomative videos explained well for a layman user...
Superb content !
Glad you think so!
So..unsupervised learning doesn't use any past/prior knowledge..
But in retail sector example where products are recommended,prior purchases are analysed??
Hey Thattepally, Unsupervised learning makes use of the input data to explore it's way to the output. Only the input is known, it has to find a pth to the output. Analysing prior purchases is a way to find patterns in data.
Hope this helps!
Good work keep it up👍
Thank you 😊 Keep learning with us..
Try to marketize your channel, You have such an awesome content on current Technologies.
Hey Mukesh, thank you for appreciating our effort! We are glad you liked our content! :)
Is there any weekend batches for python with machine learning course ... Abdullah from Aus
Hey Abdullah, we do offer weekend batches for Python, you can check out the details and the batch timings here: www.edureka.co/python
Hope this helps :)
Sir make more viDeos on machine learning Algorithm
Hey Arpit, you can check out this playlist of ML algorithms that we have already created: goo.gl/S3D6vr
Hope this helps :)
Need more explanation on reinforcement
Hey Vamshi, Reinforcement Learning is the ability of an agent to interact with the environment and find out what is the best outcome. It follows the concept of hit and trial method. The agent is rewarded or penalized with a point for a correct or a wrong answer, and on the basis of the positive reward points gained the model trains itself. And again once trained it gets ready to predict the new data presented to it.
Hope this helps!
Need more explanation on unsupervised
Hey Hemanth, Unsupervised learning is a type of machine learning algorithm used to draw inferences from datasets consisting of input data without labeled responses.The most common unsupervised learning method is cluster analysis, which is used for exploratory data analysis to find hidden patterns or grouping in data.Hope this helps :)
edureka! THQ sir got it but in video u could have explained with example little deep. Examples r ther in video but I felt it could have been little more explanation on example
Hey Hemanth, alright we got your point. We will definitely try to focus on this in our next tutorials. Thanks :)
You told that the unsupervised type classifies or groups not on the basis of past data so how come the retailer example be in the unsupervised type??
Hey Chirag, Recommender System is one the example of how the retail industry like Amazon is using unsupervised learning. The recommender system is used to recommend the products based on past searches. Hope this answers your question. Cheers!
Thanks
I have a doubt that , in reinforcement learning we are optimising the algorithm as per the different conditions??
or it is something else
Hey Ashutosh, In reinforcement learning we're training the machine through constant feedback which shall enable it to perform as per different conditions.
Hope this helps!
Sir where can we find these lectures in ppt format??
Hey Owais, thank you for watching our video. You can check out our PPTs at slideshare.net
Thanks :)
I think edureka is best for AI
Will Dialogflow Api by google fall in the category of Reinforcement ?
Hey Ankit, "Dialogflow agents use machine learning algorithms to understand natural language utterances, match them to intents, and extract structured data.
An agent (best described as Natural Language Understanding (NLU) modules) learns both from training phrases that you provide and the language models built into Dialogflow. Based on this data, it builds an algorithm for making decisions about which intent should be matched to a user utterance. This algorithm is unique to your agent.
Dialogflow updates your agent's machine learning algorithm every time you make changes to intents and entities, import or restore an agent, or train your agent."
Hope this helps!
11:10 ** unsupervised learning
at 13:16, retail shopping, promting product/bundling based on previous purchase, isn't that supervised learning? because it has history with it on what he liked & what he didnt like
You are thinking that the algorithm works only for one specific user and that is why you are confused. The algorithm actually works for millions of users at a go and the possible data may be the user, his previous purchases and so the algorithm looks at the similar kind of people and what such people would have bought extra. Take that and recommend that to the new user. That is grouping which is something an unsupervised learning algorithm does. Hope that was helpful.
Is there any coding required for machine learning.if yes how we can do it
For Machine Learning having basic knowledge of R or Python would be helpful. Also, knowledge in statistics can be an added plus point if you want to learn ML. Ceck out our ML course here: www.edureka.co/python-data-science-course
Hope this helps :)
How i can get the whole course
Hey Punit, here is a link to our ML course: www.edureka.co/data-science
Cheers :)
edureka! Thanks
@@edurekaIN Thanks
Hi...can I know what is the cost to learn ML..
Hey Kishore, nice to see your interest in Machine Learning. Edureka’s Machine Learning Certification Training using Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. For complete course details click over here: www.edureka.co/machine-learning-certification-training. For any clarification do feel to reach us at +91 98702 76459 or 1844 230 6365. Hope this helps!
Sir how can code for speech recognition machine learning ?
Please share your email id with us (it will not be published). We will forward the code to your email address.