#9 Machine Learning Specialization [Course 1, Week 1, Lesson 3]

The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. This beginner-friendly program will teach you the fundamentals of machine learning and how to use these techniques to build real-world AI applications.
This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
This video is from Course 1 (Supervised Machine Learning Regression and Classification), Week 1 (Introduction to Machine Learning), Lesson 3 (Regression Model), Video 1 (Linear regression model part 1).
To learn more and access the full course videos and assignments, enroll in the Machine Learning Specialization here: bit.ly/3ERmTAq
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[@divyakarlapudi]

it's just awesome !!

[@karthik_0180]

Yup

[@Aspiring-Data-Scientist]

Also add deep learning spacialization.

[@shubhamkumarsingh9493]

00:04 Supervised learning is the process of filling a straight line to your data using a linear regression model.
01:16 Using a linear regression model to estimate the price of a house based on its size.
02:20 Linear regression is a type of supervised learning model used for regression problems.
03:33 Classification involves a small number of possible outputs, while regression has infinitely many possible numbers as outputs.
04:45 Understanding data plot and notation in machine learning.
06:11 The input data used to train the model is called a training set.
07:41 The dataset has 47 rows, each representing a different training example.
09:13 An index I refers to a specific row in the table
Crafted by Merlin AI.

[@johnm6495]

With the training examples (x,y), why is superscript with parentheses used instead of merely using subscript?

[@uchindamiphiri1381]

I think maybe for readability

[@dr_ramy_abougreeda]

I will serve you in the future, or maybe it did.

[@hafsazulfiqar727]

sir it's a great course but how can I access labs?

[@iosifpuha6114]

you have to pay for the course

[@hafizbilal6893]

There are repos on github where students have uploaded their own labs for other's sake to practice. You can also access them. Otherwise, you would have to buy the course

[@aryanbodke9889]

cat meow, dog woof

[@spicyshizz2850]

How can I access the labs?

[@hafizbilal6893]

There are repos on github where students have uploaded their own labs for other's sake to practice. You can also access them. Otherwise, you would have to buy the course

[@nickst2797]

@@hafizbilal6893 Do you know if there are videos for Courses 2 and 3? Seems like only Course 1 is located in this channel...