Tensorflow Tutorial for Python in 10 Minutes

Want to build a deep learning model?

Struggling to get your head around Tensorflow?

Just want a clear walkthrough of which layer to use and why?

I got you!

Building neural networks with Tensorflow doesn’t need to be a nightmare. If you follow a couple of key steps you can be up and running and using Tensorflow to predict a whole bunch of stuff. In fact, you can learn how to do it with Python in just 10 minutes. By the end of this video you’ll have built your very own Tensorflow model to predict churn inside of a Jupyter Notebook.

What you'll learn:
1. Build a simple Tensorflow model to predict Churn
2. Training the model and make predictions on test data with Pandas
3. Save your model to disc and reload it to a Jupyter Notebook for reuse

Chapters
0:00 - Start
0:18 - Introduction
0:26 - What is Tensorflow
1:03 - Start of Coding
2:47 - Importing Tensorflow into a Notebook
3:48 - Building a Deep Neural Network with Fully Connected Layers
7:13 - Training/Fitting a Tensorflow Network
8:24 - Making Predictions with Tensorflow
9:15 - Calculating Accuracy from Tensorflow Predictions
9:50 - Saving Tensorflow Models
10:09 - Loading Tensorflow Models

GET THE CODE!

Links Mentioned

If you have any questions, please drop a comment below!

Oh, and don't forget to connect with me!

Happy coding!
Nick

P.s. Let me know how you go and drop a comment if you need a hand!

[ShivanS]

These videos are so good. A whole end-to-end project in 10 minutes. And a bit of humour and art tossed in there.

[kyleDoesCoding]

This is the most amazing tutorial I have ever watched. I'm not ashamed to say I sometimes require extra explaining but this guy is just spot on with his explanations.

[nonoobott]

Absolutely brilliant. End-to-end in just 10 minutes. Very explicit. Thanks for sharing

[campbellmcternan]

I normally never comment on tutorial videos but this was very excellently done! This was exceedingly concise and clear

[ZiRo]

hey mate just watched your video and thought it was super useful to my learning. You explain everything very well (look good doing so) and left out the unimportant details. Thank you for this content!

[knitronics]

This tutorial is an absolute life-saver. Well done!

[rowlandgoddy-worlu]

One thing I like about his videos is how basic he breaks down complex concepts for easy comprehension!
Having knowledge is one thing but passing that knowledge on is another. Nicholas is doing great at giving that knowledge!

[acb_gamez]

This was awesome man thanks. I got a good understanding of the flow of tensor flow and also the things I need to learn to become proficient. I def need to understand more about the different network types/shapes and their use cases, as well as the activation algorithms. Also is nice to know that I don't need to dive too deep into learning about the backpropagation and calculus because TF takes care of all of that!

[winstonyeung]

Sir, as of all your other tutorials, it is so self-explanatory and clearly defined. Thank you so much.

[michaelareay]

Excellent presentation. Straight to the point, easy to follow and well explained.

[KevinSmith-qthz]

Although this isn't an actual tutorial, it is cool to see you build a model so quickly!

[maryrooster]

Thank you! Up until now I've only done old skool supervised learning. With your tutorial I'm ready to enter the big leagues!!

[apollog]

I like how he is doing 10min tutorial but still included a humor intro

[jfecteau]

Excellent video! Concise and every step well-explained throughout.

[nickcampbell]

Didn't need to watch those 2 hours video. With your video, I was able to understand the base and the rest is just research and finding codes I need. This helped so much. Thank you! You are the best!

[akshitdayal]

A much needed video! Thank you for the great work!!

[enewhuis]

This is a perfect introduction to sharing with people on any team that works with someone working with ML. :D

[SaptadeepDutta_Ex-Xerox]

Thanks for reaching the heart of the matter (4:07) so quickly and then explaining these '4 lines' so well.

[LongNguyen-efqd]

I totally love your dedication on each videos bro !! Thanks for your hard work and keep it going !!!

[vikasyaduvanshi]

Thanx for sharing your knowledge with us bro. U explain so easily and effectively