TensorFlow 2.0 Complete Course – Python Neural Networks for Beginners Tutorial

///TensorFlow 2.0 Complete Course – Python Neural Networks for Beginners Tutorial

TensorFlow 2.0 Complete Course – Python Neural Networks for Beginners Tutorial

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Learn how to use TensorFlow 2.0 in this full tutorial course for beginners. This course is designed for Python programmers looking to enhance their knowledge and skills in machine learning and artificial intelligence.

Throughout the 8 modules in this course you will learn about fundamental concepts and methods in ML & AI like core learning algorithms, deep learning with neural networks, computer vision with convolutional neural networks, natural language processing with recurrent neural networks, and reinforcement learning.

Each of these modules include in-depth explanations and a variety of different coding examples. After completing this course you will have a thorough knowledge of the core techniques in machine learning and AI and have the skills necessary to apply these techniques to your own data-sets and unique problems.

⭐️ Google Colaboratory Notebooks ⭐️

📕 Module 2: Introduction to TensorFlow –
📗 Module 3: Core Learning Algorithms –
📘 Module 4: Neural Networks with TensorFlow –
📙 Module 5: Deep Computer Vision –
📔 Module 6: Natural Language Processing with RNNs –
📒 Module 7: Reinforcement Learning –

⭐️ Course Contents ⭐️

⌨️ Module 1: Machine Learning Fundamentals (00:03:25)
⌨️ Module 2: Introduction to TensorFlow (00:30:08)
⌨️ Module 3: Core Learning Algorithms (01:00:00)
⌨️ Module 4: Neural Networks with TensorFlow (02:45:39)
⌨️ Module 5: Deep Computer Vision – Convolutional Neural Networks (03:43:10)
⌨️ Module 6: Natural Language Processing with RNNs (04:40:44)
⌨️ Module 7: Reinforcement Learning with Q-Learning (06:08:00)
⌨️ Module 8: Conclusion and Next Steps (06:48:24)

⭐️ About the Author ⭐️

The author of this course is Tim Ruscica, otherwise known as “Tech With Tim” from his educational programming YouTube channel. Tim has a passion for teaching and loves to teach about the world of machine learning and artificial intelligence. Learn more about Tim from the links below:
🔗 YouTube:
🔗 LinkedIn:

Learn to code for free and get a developer job:

Read hundreds of articles on programming:

And subscribe for new videos on technology every day:

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By |2020-09-16T09:29:45+00:00September 16th, 2020|Python Video Tutorials|49 Comments

49 Comments

  1. Darshan Kudva September 16, 2020 at 9:29 am - Reply

    very good course tim . I am 12 and have finished ur course upto neural networks ur a great teacher , ignore the bad comments cause the people who post these comments are failures that are jealous of u , so never ever give up !!

  2. Suyash Khare September 16, 2020 at 9:29 am - Reply

    I have a doubt in the second module: Linear regression. Why did you train a regression model when the output was categorical?

  3. Pastor Joshua Tosh September 16, 2020 at 9:29 am - Reply

    Hi Tim, do you have the codes anywhere I can access?

  4. Darshan Kudva September 16, 2020 at 9:29 am - Reply

    parch means the heat of the part of the ship the passenger lives

  5. Sourabh Dhaker September 16, 2020 at 9:29 am - Reply

    1.25x will save some time

  6. Firas Abdel Ghani September 16, 2020 at 9:29 am - Reply

    How do you create this DARK Theme in Google Collab?

  7. Itay Dumay September 16, 2020 at 9:29 am - Reply

    3:39:51 12.09.2020

  8. Manikandan S September 16, 2020 at 9:29 am - Reply

    Run time 3:37:00 – I think we have to compile the model every time before we do a fit. Otherwise it just memorize the previous epochs and use it for next iterations. In this case I believe that 92% accuracy of 1 epochs is the same as the addition of previous epochs i.e 10+8+1 = 19 epochs

  9. computer brand September 16, 2020 at 9:29 am - Reply

    Sir in CNN the filters extracts from the image or generate random numbers?

  10. Patrick Hansen September 16, 2020 at 9:29 am - Reply

    Hi, I hope its okay I share this here – I share it on my recommendations as that's where it's most likely for me to find people with similar interests to myself.

    If not please tell me and I won't do it again 🙂

    I found something I think is interesting, its low-risk very uncertain reward, akin to early bitcoin mining. You are going to think it’s a scam at first, but I dare you to engage your faculties at least enough to investigate the surface value-proposition, such as visiting their website or thinking it through. I am not affiliated with the project and only rewarded in the same way you can be if you join.

    It’s a blockchain/crypto currency project that attempts to reach the masses and levitate some of the short-comings of mainstream cryptos such as Bitcoin. Its not launched yet, so would be akin to joining Bitcoin before it was traded on the exchanges.

    You need an invitation password to join, here is the one linked to my account: [Godsk]. Its called [Pi Network] and you if you are interested you can visit their webpage or read their white paper, there they explain everything. The value for you is that you are able to mine pi with your mobile device, again much the same as you were originally able to mine Bitcoin with your CPU and GPU, however, the mining is tied to the device and not its computational power. Again, everything is explained on their site and their white paper, Medium also has a really good article on [Pi Network].

    It’s super easy, you can find the application on the app store. You don’t pay or give anything, expect the invitation key: [Godsk]. And you can test it out in minutes, if you don’t like it, just uninstall.

  11. computer brand September 16, 2020 at 9:29 am - Reply

    So the lambda returns a function right?

  12. Zara z September 16, 2020 at 9:29 am - Reply

    Something has been bugging me… I mean should I dump Pycharm (remove it) and start using Google Colab???
    I'm confused

  13. Zeesh009 September 16, 2020 at 9:29 am - Reply

    ink background should be black or dark color so its easier on the eyes

  14. Rick Sanchez September 16, 2020 at 9:29 am - Reply

    2:49:09 this bothered me, just admit you used a calculator to double check

  15. computer brand September 16, 2020 at 9:29 am - Reply

    what is the difference between linear_est.evaluate and linear_est.predict?

  16. computer brand September 16, 2020 at 9:29 am - Reply

    tf.shape is kind of matrices, like first element represent the numbers of rows and second columns

  17. computer brand September 16, 2020 at 9:29 am - Reply

    are Deep learning and neural net same thing?

  18. Nothingness September 16, 2020 at 9:29 am - Reply

    Am I the only 13 Yr old here?

  19. Vignesh September 16, 2020 at 9:29 am - Reply

    48:51 – first stop

  20. 8th Floor Harmony September 16, 2020 at 9:29 am - Reply

    Is Gradient Tape explained in this tutorial ? Thanks in advance : )

  21. Alperen Enes Bayar September 16, 2020 at 9:29 am - Reply

    Awesomesauce

  22. MPR info-tech September 16, 2020 at 9:29 am - Reply

    Sir Inow python coding using tensorflow coding python and tensorflow coding are same

  23. serge133 September 16, 2020 at 9:29 am - Reply

    Actually Enjoyable

  24. Slawomir Gontarek September 16, 2020 at 9:29 am - Reply

    Whay I can not translate your video on other language?

  25. Chris Choir September 16, 2020 at 9:29 am - Reply

    You are a great teacher

  26. Chris Choir September 16, 2020 at 9:29 am - Reply

    Why does anyone need to learn AI or ML or TensorFlow? can't ML just automatically do everything for you?

  27. David Mccary September 16, 2020 at 9:29 am - Reply

    1:27:20 thinks back to 6th grade no! Noo!

  28. John White September 16, 2020 at 9:29 am - Reply

    Having the TF documentation and tutorial pages in video format is pretty helpful. Thanks!

  29. SOUL SAMA September 16, 2020 at 9:29 am - Reply

    You lost me at RNN completely. I thought this was a Beginners Tutorial.. Too confusing, You gotta dumb it down for us new folks.

  30. shubham dhawan September 16, 2020 at 9:29 am - Reply

    You rock bro <3

  31. Ankit Sagar September 16, 2020 at 9:29 am - Reply

    Hi Tim,
    Needed an advice: I have been into javascript for long, and now thought of diving into ML. I could see we have Tensorflow.js also available now. What's your recommendation? Is it any good? or shall i continue learning Python before diving here.
    Great tutorial btw (y)

  32. GreatGamer975 September 16, 2020 at 9:29 am - Reply

    Bookmark 1:12:50

  33. Ifedayo Karim September 16, 2020 at 9:29 am - Reply

    Very nice content

  34. shifa asif September 16, 2020 at 9:29 am - Reply

    Where can I find all these codes? Please answer as soon as possible

  35. Aveesh Sinha September 16, 2020 at 9:29 am - Reply

    Let's learn this I'm 13 🙂

  36. Aryan Mishra September 16, 2020 at 9:29 am - Reply

    Thumbs Up! What A Clear Explanation and also By The Way You Cared Of Other People Having A Crapy and old school computer by using google colaboratory just loved this and recommend to all the people who want to hop into this field. tim made it vert-very easy for beginners and intermediate programmers to understand tensorflow by heart. Thumbs Up!!

  37. Krunal Degamdiya September 16, 2020 at 9:29 am - Reply

    Thanks a lot for making it on youtube.😍👌👍

  38. upendra jena September 16, 2020 at 9:29 am - Reply

    ValueError: Feature (key: age) cannot have rank 0. Given: Tensor("linear/linear_model/Cast:0", shape=(), dtype=float32) ………………………………….i am getting this error even though i hav copied cells of the same codes u hav written ,while checking accuracy of result cell no18

  39. Aidan Sunbury September 16, 2020 at 9:29 am - Reply

    Tech with tim!

  40. Selwyn September 16, 2020 at 9:29 am - Reply

    I've heard more voice cracks than info I've learned

  41. Sagi Mor September 16, 2020 at 9:29 am - Reply

    Well done Tim, thank you.

  42. Priyanshu Saraf September 16, 2020 at 9:29 am - Reply

    Is he the best teacher ever?

  43. TFW September 16, 2020 at 9:29 am - Reply

    Pac man ghosts are actually random, is that still AI?

  44. Jared Willman September 16, 2020 at 9:29 am - Reply

    Hey man, just wanted to say you make the internet awesome, thanks

  45. Андрей Журавель September 16, 2020 at 9:29 am - Reply

    Tech with him

  46. freeideas September 16, 2020 at 9:29 am - Reply

    26:26 Beavis and Butthead would laugh here

  47. Amir mohammad Naderi September 16, 2020 at 9:29 am - Reply

    Great effort, thank you very much. Although if you don't mind a little feedback, I have to say you have a few mathematical mistakes. for example in the introduction and definition of vectors, matrices and tensors (I haven't finished the course yet, but in the first hour these were the only mistakes I noticed). Although this is somewhat common among the programmers and developers who do machine learning (being more practical and less theoretically on top of stuff), but I think if you are teaching something it should be correct. But otherwise this is a great course and I really thank you for your time and effort. Keep up the great work 🙂

  48. Harsh Shukla September 16, 2020 at 9:29 am - Reply

    FOR TENSORFLOW 2.0
    For running seesions at : 57:03
    with tf.compat.v1.Session() as sess:

    print(tensor0.eval())

  49. Shashank C September 16, 2020 at 9:29 am - Reply

    Thank you brother! Amazing work

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