Basic Linear Regression | Tensorflow | S1 E6 | Absolute beginners | Python | Machine Learning

Linear regression is the most common tool for predicting continuous target. Tensorflow helps beginners get access to all the tools such as Gradientdescent and others so that they can perform Linear regression easily.
In this video, I will explain each and every cell of the jupyter notebook so that you understand every bit of the notebook without being left in between.

In order to get the best understanding of the notebook, please watch all the videos that I have uploaded in the channel for Linear Regression. S1 - series 1.

FAQs
1. Which is better Sklearn or Tensorflow?
2. How can we scale the model if we have more than one x_data columns, example x_data1 , x_data2, etc?
3. Why can't we get zero error even after a large number of epochs?

Questions about channel.
1. Can you make individual help videos?
2. Can you give personalized help if I want?
3. Can we ask help for advanced topics or research papers?
4. Do you read all comments?
5. Subscribe. WHY?
6. Comment. WHY?

Answers:
1. Depends on your priorities. If you want faster implementations and are still learning and don't want to experiment much, go for sklearn. Tensorflow gives you more tools and so free to experiment. Helps more than sklearn, if you want to learn more.
2. Just use more variables. If a lot of people will have this doubt, I will make another video explaining this and some related concepts.
3. Because data always has noise. Data is not in a straight line so there will always be some distance for some points and so residuals will not be equal to zero.

Channel questions.
1. Yes, ask me on Facebook or here in the comment section.
2. Yes, if that is what you want.
3. Yes, if I it is relevant.
4. Yes, I do.
5. It is very common in machine learning students to leave some doubts for later whenever they encounter an advanced or difficult topic. Even though there is nothing bad in that because machine learning concepts are difficult at times, but since those concepts are important, they come to haunt you back. So, if you have notifications for my channel, on, I am pretty sure that some of my videos that I will post will be on the topics that you have missed or are still not clear. The best part of this exercise will be that on some random day you will have an important concept clear without even explicitly going to YouTube to clear those concepts out.
6. Comments help both of us connect inside YouTube. If you post a doubt, I will try to answer that doubt as a reply. If the doubt is good, I will make a video. Yes, I definitely plan to make videos explicitly on complex doubts that are difficult to understand without pictorial demonstrations and a step by step approach. I think this will help the community in the best possible way.
Your comments will also help me know my mistakes and how can we grow as machine learning enthusiasts.

Post queries and discuss on:

[shifa]

This channel is It's blasphemous that there are little amount of views on this channel. Amazing way of explaining and easy to understand 👍. Thank you so much.