Learn TensorFlow and Deep Learning fundamentals with Python (code-first introduction) Part 1/2

Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you’ve come to the right place.
After this two-part code-first introduction, you’ll have written 100s of lines of TensorFlow code and have hands-on experience with two important problems in machine learning: regression (predicting a number) and classification (predicting if something is one thing or another).
Open a Google Colab (if you’re not sure what this is, you’ll find out soon) window and get ready to code along.
Sign up for the full course - dbourke.link/ZTMTFcourse
Get all of the code/materials on GitHub - www.github.com/mrdbourke/tens...
Ask a question - github.com/mrdbourke/tensorfl...
See part 2 - • Learn TensorFlow and D...
TensorFlow Python documentation - www.tensorflow.org/api_docs/p...
Connect elsewhere:
Web - www.mrdbourke.com
Livestreams on Twitch - / mrdbourke
Get email updates on my work - www.mrdbourke.com/newsletter
Timestamps:
0:00 - Intro/hello/how to approach this video
1:50 - MODULE 0 START (TensorFlow/deep learning fundamentals)
1:53 - [Keynote] 1. What is deep learning?
6:31 - [Keynote] 2. Why use deep learning?
16:10 - [Keynote] 3. What are neural networks?
26:33 - [Keynote] 4. What is deep learning actually used for?
35:10 - [Keynote] 5. What is and why use TensorFlow?
43:05 - [Keynote] 6. What is a tensor?
46:40 - [Keynote] 7. What we're going to cover
51:12 - [Keynote] 8. How to approach this course
56:45 - 9. Creating our first tensors with TensorFlow
1:15:32 - 10. Creating tensors with tf Variable
1:22:40 - 11. Creating random tensors
1:32:20 - 12. Shuffling the order of tensors
1:42:00 - 13. Creating tensors from NumPy arrays
1:53:57 - 14. Getting information from our tensors
2:05:52 - 15. Indexing and expanding tensors
2:18:27 - 16. Manipulating tensors with basic operations
2:24:00 - 17. Matrix multiplication part 1
2:35:55 - 18. Matrix multiplication part 2
2:49:25 - 19. Matrix multiplication part 3
2:59:27 - 20. Changing the datatype of tensors
3:06:24 - 21. Aggregating tensors
3:16:14 - 22. Tensor troubleshooting
3:22:27 - 23. Find the positional min and max of a tensor
3:31:56 - 24. Squeezing a tensor
3:34:57 - 25. One-hot encoding tensors
3:40:44 - 26. Trying out more tensor math operations
3:45:31 - 27. Using TensorFlow with NumPy
3:51:14 - MODULE 1 START (neural network regression)
3:51:25 - [Keynote] 28. Intro to neural network regression with TensorFlow
3:58:57 - [Keynote] 29. Inputs and outputs of a regression model
4:07:55 - [Keynote] 30. Architecture of a neural network regression model
4:15:51 - 31. Creating sample regression data
4:28:39 - 32. Steps in modelling with TensorFlow
4:48:53 - 33. Steps in improving a model part 1
4:54:56 - 34. Steps in improving a model part 2
5:04:22 - 35. Steps in improving a model part 3
5:16:55 - 36. Evaluating a model part 1 ("visualize, visualize, visualize")
5:24:20 - 37. Evaluating a model part 2 (the 3 datasets)
5:35:22 - 38. Evaluating a model part 3 (model summary)
5:52:39 - 39. Evaluating a model part 4 (visualizing layers)
5:59:56 - 40. Evaluating a model part 5 (visualizing predictions)
6:09:11 - 41. Evaluating a model part 6 (regression evaluation metrics)
6:17:19 - 42. Evaluating a regression model part 7 (MAE)
6:23:10 - 43. Evaluating a regression model part 8 (MSE)
6:26:29 - 44. Modelling experiments part 1 (start with a simple model)
6:40:19 - 45. Modelling experiments part 2 (increasing complexity)
6:51:49 - 46. Comparing and tracking experiments
7:02:08 - 47. Saving a model
7:11:32 - 48. Loading a saved model
7:21:49 - 49. Saving and downloading files from Google Colab
7:28:07 - 50. Putting together what we've learned 1 (preparing a dataset)
7:41:38 - 51. Putting together what we've learned 2 (building a regression model)
7:55:01 - 52. Putting together what we've learned 3 (improving our regression model)
8:10:45 - [Code] 53. Preprocessing data 1 (concepts)
8:20:21 - [Code] 54. Preprocessing data 2 (normalizing data)
8:31:17 - [Code] 55. Preprocessing data 3 (fitting a model on normalized data)
8:38:57 - MODULE 2 START (neural network classification)
8:39:07 - [Keynote] 56. Introduction to neural network classification with TensorFlow
8:47:31 - [Keynote] 57. Classification inputs and outputs
8:54:08 - [Keynote] 58. Classification input and output tensor shapes
9:00:31 - [Keynote] 59. Typical architecture of a classification model
9:10:08 - 60. Creating and viewing classification data to model
9:21:39 - 61. Checking the input and output shapes of our classification data
9:26:17 - 62. Building a not very good classification model
9:38:28 - 63. Trying to improve our not very good classification model
9:47:42 - 64. Creating a function to visualize our model's not so good predictions
10:02:50 - 65. Making our poor classification model work for a regression dataset
#tensorflow #deeplearning #machinelearning

[@mrdbourke]

Friends, here are some helpful links: • 🤓Sign up for the full course (40+ hours of TensorFlow) - dbourke.link/ZTMTFcourse • 💻Get all of the code/materials on GitHub - www.github.com/mrdbourke/tensorflow-deep-learning/ • 📖Read the course materials in beautiful book form - www.learntensorflow.io • ❓Ask a question - github.com/mrdbourke/tensorflow-deep-learning/discussions • 💬Get live captions (if using Google Chrome) - support.google.com/chrome/answer/10538231?hl=en Happy Machine Learning!

[@hrishipaul5424]

You are awesome dude!!:) Love from India

[@josbexerra8115]

Excellent sir...., it would be very kind of you to activate the subtitles of your wonderful course

[@maohejiang6485]

I’m gonna buy the course, thanks

[@alabiobin128]

Can i please get the link to the discord chat?

[@vedantmahida4996]

Hey Daniel, is it good idea to watch this tutorial on tensorFlow before continuing Deep learning portion on ZTM - Data Science and Machine learning course 2022? I think this youtube tutorial does more indepth. So it may help increase the speed of learning in Udemy course

[@mrdbourke]

Get ready to dream in tensors.

[@munasheruvinga5458]

Thank youu soo much Daniel!!!!!!!

[@ArjunKumar123111]

I can only imagine how many hours you've put into it. You're a legend Dan!

[@CodeEmporium]

The mind is a matrix

[@chihpoc]

@@CodeEmporium the mind is a tensor :)

[@ayencoscolfield3312]

Great job

[@FarisSkt]

I cant thank you enough for all the efforts you do to teach ML. You can’t find quality content like this anywhere else, for free.

[@mrdbourke]

You're welcome Faris! Enjoy legend!

[@nagamohith3467]

Yes He is a legend

[@tariqahassan5692]

For me, this is the most amazing lesson about TensorFlow on KZbin ever .. Many thanks, Daniel..

[@TeddyWarMan]

this style of teaching is so effective for people like me who have ADHD, thank you so much you absolute ledgend

[@mrdbourke]

It's how I like to learn too! Thank you for the kind words Rohan, enjoy!

[@paulntalo1425]

I agree 120%. Am baffled. The voice and quality are just legendary

[@lifehope4201]

Rohan bhai.....ADHD....?

[@LaurentLaborde]

you can follow a slow 10h course with ADHD ? ^^

[@wgabrys88]

Hahaha, same, it's good because instead of providing definition, the author goes to Google and tries to explain to us what it means - it's like watching a movie, you don't know what google will display and how the author will explain that to us - dopamine driven course 🎉

[@chrisvagkidis3865]

Amazing tutorial Dan! Step by step and great explanations. The fact that you show how exactly you are searching something when you do not know how to use a specific function helps the audience to become "self-taught". Thank you so much!

[@ajayjoshi45]

Hats off man, great tutorial and great way of teaching, My search for tensorflow turotial ends here until I finish up with 10+4 hours of your tutorials. Thanks a ton and great service to machine learning enthusiasts.

[@panashemureyi1599]

I'm loving the intro, it feels like we are figuring out everything together. makes it much more approachable for me, a beginner. really appreciate it.

[@Mark-nm9sm]

Im 5:47:41 hours deep, I have been wanting to say this from early on but I wanted to make sure I am not too fast to talk. You are an excellent teacher, regardless of the topic you are teaching in this video, the way you teach is exactly the way it should be done. You arouse our critical thinking and you get us to make questions. You might not be here in this room with me but i feel more energy from you than from my university teachers in person💯💯💯

[@shivambakshi8230]

Even better then paid courses ! Thank you Daniel for such amazing stuff.

[@Nirex_]

Awesome course to get up and running with TensorFlow specially if one has a good theoretical backbone of the topics explained. Perks to Daniel Bourke, Just fantastic!

[@medicineformelancholy9033]

Hey Daniel, I'm studying neuroscience at uni currently and I just wanted to say thanks for the great tf series. I'm doing data analysis for the lab I'm working in and have been trying to implement some deep learning techniques to speed things up. This channel has been the most helpful resource by far for my own exploration of ML, so keep on, brother, and thanks again.

[@jag2709891]

This is amazing, first video I’ve seen of this kind that the person uses simple language whilst telling you the complicated form so you don’t get bewildered when doing further research; bravo sir!

[@vedmodikauratg1865]

Love the way you keep me engaged throughout the video by sharing our enthusiasm. Amazing Job! You have my subscription

[@ComputerScienceWithBas]

After going through so many complicated and advanced tutorials (PS :- Didn't understand all the stuff there, this video literally made every concept clear). HATS OFF to such great creators like you sir !. Thank you so very much. Please make more advanced long tutorials so that we can become experts as well. Thank you !

[@aminroustapour1011]

Dear Daniel, I wanted to thank you for the effort you put into making this video. I was learning machine learning when I came across your videos. I used it a lot and my learning process increased greatly. I owe you❤

[@Rykker1]

Learning at this fully explained pace really makes the concepts stick, great job man.

[@yogeshhasabe4931]

Absolute Biggy !! Great Initiative Daniel to post it on the channel. Going to share it with everyone out there and recommending the course too

[@yasthirdhewnarian6531]

This video is extremely underrated my man. Amazing job! Please keep on making more videos. You are a terrific teacher

[@habeebrahman9790]

Amazing

[@piyushpandey8509]

Just completed this course, there is a certain poise in how you teach man. Amazing! will be learning more from you in future!

[@mkhadka123]

It's like finding exactly what you're looking for and finding GOLD content for that matter. I feel lucky to be alive in an era where knowledge such as this one is given for free. Thanks!

[@pinehteshapple3666]

NOTE: If you are getting a TypeError at 4:39:49 while fitting the model you will need to add tf.expand_dims() I don't know why but it worked for me. example: model.fit(tf.expand_dims(x, axis=-1), y, epochs=5) Edit: I did some studying the reason this error was there because the training data and evaluation data are not of the same dimensions and/or number similar to when tried to dot product the matrices.

[@ahmadbodayr7203]

Thank you man god bless you

[@pinehteshapple3666]

@@ahmadbodayr7203 I did some studying the reason this error was there because the training data and evaluation data are not of the same dimensions and/or number similar to when tried to dot product the matrices.

[@bushbasher9791]

bcz dense expecting 2d tensor , maybe they updated that

[@akoub5270]

thanks a lot , i really spent a lot of time trying to figure out what was the problem . thanks for sharing

[@amoghrgowda4652]

Thanks man

[@Williamegert]

Your teaching method is superb! Typing along with you, in additional to how thoroughly and clearly you explain everything, is a crucial supplemental learning dimension. I'm amazed here not just about how much I know but how much I understand. Thanks Daniel!

[@mrdbourke]

You’re welcome legend! Thank you

[@linusbergman7881]

I've bought various course packages and tried vocational uni, but quit because it's too fragmented and I end up having to paus and google stuff every 30 sec or so just to feel like I'm not missing anything important. Always on point, very John Dewey with encouraging experimentation and without skipping vitalt bits of information. Excellent progression all the way from the start. The first 55min or so of introduction and answering the important didactical questions (what, why, when, how.. and so on) is REALLY good and I so wish that more educational material had that sort of info at the start of courses. I'm sort of an aspie-kind of person and just rushing through things can be really upsetting and stressful. Will definitely get into the payed material once I've exhaused everything I can from this video.

[@Asif-jd2km]

Seven months later I find your video from KZbin recommendations so helpful and easier to understand I’m a self thought programmer so I can’t understand what others KZbin video’s saying and confused and drop the topic and didn’t look at them, but your video is so understand and very details, One sub from me:)

[@leonardopetribu7207]

*A playlist with 60 videos of 10 min each* Me: meeeh, not today... *A single video with a 10 hours marathon* Also me: LET'S GO FOR IT!!

[@mrdbourke]

If I could have made this one single video, I would’ve

[@leonardopetribu7207]

@@mrdbourke did I hear 15 hours of pytorch?? 😅😅 But seriously, congratulations for the content bro

[@TheRealDefacto]

Dan! this is awesome! Thank you for putting in this much effort! You're a really gifted teacher.

[@mrdbourke]

Thank you so much!

[@actualBIAS]

Just finished this masterpiece. Took me 2 days. You re wonderful. Thanks so much for sharing.

[@GaMiNGYT-dc2cf]

Man ...Even a small kid can understand these videos...CRYSTAL CLEAR Explanation and He was upto the point!Awesome video and I never found a video like this one and I doubt if i would find something as good as this in the future

[@thenewculture2359]

this man was sent from god

[@munasheruvinga5458]

Yessss, for real!!!

[@ayencoscolfield3312]

You are absolutely correct on all grounds , in fact the man is a small god himself

[@patricksfeir6947]

Is he Lucifer ?

[@mazerat3122]

For those who had a ValueError right from the getgo There is one extra line that he didn't have to add with his version of TensorFlow model = tf.keras.Sequential([ tf.keras.layers.Input(shape=(1,)), ###This extra line tf.keras.layers.Dense(1) ]) model.compile(loss=tf.keras.losses.mae, optimizer=tf.keras.optimizers.SGD(), metrics=["mae"]) model.fit(X, Y, epochs=5)

[@sshubam]

Thankyou so much Daniel ! for making this Introduction to TensorFlow course free on KZbin, your way of teaching is really good and the code along lessons are easy to understand. I am nearly done with this KZbin part and now i just bought this course. Loving it so far ! Great job !

[@rayyanamir8560]

The full course is on udemy

[@amanupadhyay8765]

I just had a new project assigned to me - research on DL algorithms for our clients. I have done dozens of courses from EdX and Datacamp to Udemy. Hands-down, this is the most phenomenal course I've seen. This course is even better than the 2 courses I've loved the most since I started learning - Python for everybody by Dr Chuck and Excel skills for Business Specialization on coursera by macquarie. Bravo Daniel! I hope you keep producing endlessly brilliant content like this all your life.

[@gautam.pamnani]

I am Computer Science student, this semester we were properly introduced to ML as a subject. I was searching for a tf courseware on NN & the moment I saw this video, I was hooked ! It's been 7 hrs now (used my entire weekend), coded along, learnt so much along the way - right from the basic algebra (vectors, scalars, tensors, matrices...) all the way through ML and NN. I'll complete this as well as part 2 before another weekend ! LEARNING HAS BEEN SO MUCH FUN & INTERESTING BECAUSE OF YOU, SIR 'D. BOURKE'. Thanks a lot for such awesome content, your hard work shines throughout the course curriculum. I recommend everyone to justify his hard work by completing the entire tutorial along with Programming.

[@shatandv]

Yo, this is sick, Daniel. Thank you so much! Would love a similar one for PyTorch, if you are thinking about doing one :)

[@steevenkenny9791]

Sir , you are a gift for us learner... I can't thank you enough for the excellence you give us.. thank you

[@Ayesha-wf3sy]

This deep learning course is incredible. It would be really helpful in solving problem in our final year project. Thank you so much for all this content.

[@arijitghosh2497]

This is amazing, waiting for part -2, your journey is inspiring man! great going looking forward to some great content

[@amansinghbhadauria2818]

I couldn't find part 2, where is it?

[@mdhidayat5706]

Wow pure dedication to teach deep learning! Love your videos.

[@mrdbourke]

Thank you Md!

[@trendsetters89]

This is exactly what I was looking for.. Kudos to your ability to put your feet in the shoes of the viewer (especially someone programming illiterate like myself)

[@castle_of_jokes]

loved this course so much!! I actually bought it on udemy LOVED IT thanks Daniel and any one who helped in the making of this course !!!!

[@victoriawaldorf6336]

Daniel, thank you so much for your course! After completing this tutorial, I easily got a job offer because Im able to describe all deep learning concepts in details!

[@akshayraoch]

For real ?

[@KenJee_ds]

YOOOO this is some serious stuff!

[@vincentvanpuyvelde3931]

1:02:24

[@universal4334]

But you never do stuff like this 😅

[@mrdbourke]

Ken Jee in the house! Big dog’s gotta eat!!

[@manojrana009]

True

[@Chetan_Hansraj]

cant thank you enough , just goes to show if you have a good teacher like Daniel, even machine learning , Ai and high end concepts become clear in the seekers mind , god bless bro , keep up the good work , thank you :))

[@LinggogeniAndalas]

Yeah... you are my online lecturer now, this is an increase in my credit hour, thanks so much Daniel...

[@anantvaid7606]

Hey Daniel!! This is the first video, literally first on deep learning that didn't make me sleep whatsoever... I was hooked to the screen and was able to grasp everything so easily... Kudos to you for your hard work and such a beautiful explanation of concepts... Keep making such awesome videos and we promise we'll leverage this knowledge for the best of data science... All the very best and we love you 💯

[@mrdbourke]

So happy to hear you enjoyed! I really appreciate it! Plenty more to come :)

[@ananya__f]

@@mrdbourke sir please make such a long hourse tutorial for #machine_learning_beginers

[@rajatkmitra]

Daniel, if your were around when I was a student at my university and I happened to have you as a teacher.... well.... This is an amazing set of lectures! YOU my friend are well on your way to creating the next generation of world class scientists!! Keep up the great work!!!

[@mrdbourke]

Thank you Rajat! I really appreciate it!

[@marwenmejri6435]

Oh man you re a legend. I think this is the most documented and organized tensorflow tutorial on KZbin

[@andydataguy]

This was the best course ad I've ever seen. Love it!!! You've come a long way in your journey TF journey 🙏🏾🚀

[@hazeezadebayo]

6:44:00 gave some BORAT vibes and i actually smiled. thanks so much for the content. to say your style of teaching is amazing would be an understatement.

[@mrdbourke]

Thank you Azeez! I really appreciate it :)

[@b.k.7363]

No has ever taught ML/DL better....seriously, this is my 4th attempt at ML and I think I might just get it this time! The teaching structure is absolutely beautiful. I am at 5:20:45 and I WILL comment when I get to the end.

[@mrdbourke]

Thank you! Glad you’re enjoying! Keep learning legend! Can’t wait to hear when you’re done

[@b.k.7363]

@@mrdbourke Wooho! Done with video 1! Heading on to video 2!

[@mrdbourke]

@@b.k.7363 outstanding effort! Keep going!

[@niteshkumar0202]

Friends I have been following this video for last 5 days to complete the code with practice simultaneously

[@mrdbourke]

Keep going guys! You’ve got this!

[@drm8164]

Is it all I need to get ready for Tensorflow certification examen ???

[@sunnymoon5262]

AWhh!! Love your motto "If in doubt ; run the CODE!"

[@bhbh476]

this man amazes me every time. thank you so much. i hope this course also release on udemy. in this way i can buy this course and learn new things

[@mrdbourke]

Thank you! Treat these videos (part 2 coming soon) as the warmup for the Udemy version

[@saptarshisanyal4869]

"Thank You" will be such a understatame for this gem. You have just made a brilliant tutorial in TensorFlow which will not only help the beginners to get themselves acquiented but also, enable them to know how to actually work out on a problem by searching and interpretting the results and again tweaking the model. Thank you - million times. Love from India.

[@mrdbourke]

You’re welcome Saptarshi! I really appreciate it legend

[@tejpreetsingh870]

Best video I watched on whole internet if you want to start learning Tensorflow or deep learning

[@mulungisteven3122]

i like the ending part😀. "THE MISSING PART". bro its like a movie, very amazing and understandable

[@drm8164]

Is it all I need to get ready for Tensorflow certification examen ???

[@dassad9777]

1:33:00 To see the difference between normal, and uniform distribution we can visualize it on plot: import tensorflow as tf import matplotlib.pyplot as plt random_generator_set = tf.random.Generator.from_seed(43) random_tensor1 = random_generator_set.uniform(shape=(2,20000)) random_tensor_color = random_generator_set.normal(shape=(1,20000)) random_tensor_size = random_generator_set.normal(shape=(1,20000)) plt.scatter(random_tensor1[0],random_tensor1[1],s=random_tensor_size*2000,c=(random_tensor_color),alpha=0.01,cmap='Blues') random_generator_set = tf.random.Generator.from_seed(43) random_tensor2 = random_generator_set.normal(shape=(2,20000)) random_tensor_color = random_generator_set.normal(shape=(1,20000)) random_tensor_size = random_generator_set.normal(shape=(1,20000)) plt.scatter(random_tensor2[0],random_tensor2[1],s=random_tensor_size*200,c=(random_tensor_color*1000),alpha=0.42,cmap='Blues')

[@ansharora3248]

I learnt TensorFlow from this video a week back but forgot to comment. This stuff is too good. Shared it in my community. Every course developer should learn from you. Thanks a lot!

[@florentakpro8799]

yes but tooo long

[@akshayakumars2814]

I learnt the basics, you are my master, much love from India ♥️🙏

[@saikatsom4450]

it was really a great course to start off with deep learning. enjoyed the course and learned a lot. Thank you so much for sharing your knowledge in a great way.

[@sunderrajan6172]

Great work! I like the teaching method and have couple of questions/observations. 1. In your NN diagram there is a connection between Hidden to Hidden - not sure if you kept it to illustrate skip connections/dropouts and Layers; 2. In the type of learning, adding Reinforcement Learning would be nice

[@aaronbm4354]

Love the way you say beautiful after each execution of code ,it inspires to have passion in coding.

[@mrdbourke]

Working code is a beautiful thing

[@mba2000sapna]

Superb content. Effective teaching style. Anyone without ML / python background can easily understand it. Great efforts.

[@edwinnderitu7281]

In 2022 this is the best content on Ml in the internet. Thanks a million

[@Vasko10100]

The fact that you have ZERO dislikes tells you that this is PURE GOLD. I think that these videos and the whole course should be recommended by the Tensorflow official team for learning TensorFlow. Keep up the good work!

[@mrdbourke]

Thank you so much Vasko! That’s a very big compliment! Plenty more to come :)

[@demonsawakening]

lol, you jinx it

[@THEVIERAOS]

@@demonsawakening Makes me wonder what there was to dislike. Wish KZbin would make you give a reason for the dislike.

[@niksvp93]

I just love the articulation and the analogies with which you teach, Daniel. I don't think I've ever seen anyone teach anything with such an insight. You amaze me and I just love your enthusiasm. I'm looking forward the course in Udemy as well! :D

[@mrdbourke]

Thank you thank you thank you Nikhil! Those are some very big compliments. You've put the biggest smile on my face! Udemy version coming soon

[@niksvp93]

@@mrdbourke You've totally nailed it! :D

[@Jordan-sp5lw]

@@mrdbourke whens the udemy course coming

[@robinfelix3879]

@Nikhil Vattipalli is the course on Udemy and ZTM is same?

[@LovingLego]

Thank you for your tutorial. I'm a newbie to python programming, I used NodeJs for TensorFlow, and this tutorial is straightforward to understand. 🍻

[@laurentk2033]

This is the third course that i've watched so far and I have to say this is the best of all, seriously if you are hesitating with another one I swear this course is lit

[@mrdbourke]

Thank you so much Laurent! I appreciate it!

[@majduddinalboon6379]

Thank you , man you are the i am 13 and interested in machine learning but whatever course i find is so complicated and explains with maths that i can not understand but you unlike them all you go throughout the thing without alot of complicated maths and explain it pretty well thanks man you are the best

[@mrdbourke]

You’ve got this Majduddin, code along and research more when you need

[@majduddinalboon6379]

@@mrdbourke thanks man you are a role model for me now

[@joelmartinez2505]

I cant believe this is free, thank you

[@mrdbourke]

Enjoy Joel!

[@cloud_c5222]

This is spectacular Daniel. Thanks for creating this course

[@acnice_]

This is the best crash course I've ever taken in deep learning, thank you Dan... Please I'd also love you to help me fix a bug during plotting, i can't seem to wrap my head around it. Thanks :)

[@daksheshgupta7045]

This is exactly what I was looking for, a good concise tutorial. Thanks! also, first comment heh.

[@GCiambrone]

Thank you so much for this invaluable content, I'm going to be going through the whole thing!!

[@mrdbourke]

You're so welcome! Enjoy my friend! Part 2 coming soon

[@Skitty_Jones]

Holding Point. 4:45:57 / 10:15:27 Thanks for the Content! I appreciate your Favor.

[@muhammadanas7698]

Amazing Course! - Understood everything very clearly

[@maharshioza2403]

In Hinduism we believe teachers are not just a human being but God.....you are my God as far as these topics are concerned 🇮🇳🙏👍🏻😂

[@phonethiriyadana]

this is great. I was waiting for the course to be released on Udemy. now I can already start and just continue once it is released :D

[@mrdbourke]

These videos (part 2 coming soon) will get you warmed up for the full version!

[@birajparikh3367]

Hey Daniel, Will you release this course on udemy?

[@girmaygebremeskel8419]

Thank you brother, the thing I like the most about you is, you don't get tired of writing each and every code repeatedly. Respect!!

[@mrdbourke]

Thank you Girmay!

[@dominikmazur4196]

Daniel you are the Master. Thank your for your effort👍💪🙂

[@act0r399]

I don't know English enough, but for this video, I ready to learn enough:)))

[@mrdbourke]

You got this!

[@act0r399]

@@mrdbourke thanks:)

[@mohdanasnadeem1236]

Me while coding after watching this entire course : *Hmm*

[@messitcool]

witcher vibes. lol

[@mohdanasnadeem1236]

@@messitcool 😂

[@haralc]

Man! Just for that introduction and "Tensorflow" suspense and animation, I'll sign up for the full course!

[@sumantthakur2383]

Every bit of this video is awesome but best part about the video were the small pauses after question + google that gave me a chance to understand/analyse what code is doing and then checking what you say to know if I was wrong or right. This helps me to remember concepts/ideas for longer periods. Thank you Daniel for this amazing tutorial

[@mrdbourke]

Thank you Sumant! Glad you’re enjoying

[@eblade4542]

What would be the pre requirements or knowledge we should know before starting this video, I’ve just started learning data science around a month ago, would I be able to learn this or should I watch something before this.

[@mrdbourke]

If you’ve got experience with Python code + a little ML you should be good to go! I’d even try it out and see how far you get before you get stuck. If you need to go learn something and come back, these videos will still be here Otherwise here’s the list of formal prerequisites: github.com/mrdbourke/tensorflow-deep-learning#prerequisites

[@venkatyalamati3285]

Great... The best tutor on KZbin for tensor flow❤

[@arunrajiitbaero]

I urge UN to honor Daniel with the best teacher award.. much much better than university teaching

[@cemtekesin9033]

Is it just me or there are no like/save buttons right now?

[@Wezuzamc]

same. I wanted to save it on my playlist on youtube but there is no such option :

[@mrdbourke]

Not sure what’s happening here! Could be loading in the background

[@deino4753]

0:12 "I don't want to keep you too long." Sure you don't.... 🤔 Love your content though.

[@mrdbourke]

hahahaha

[@Leonardo_A1]

Best regards and a lot of thanks to you from Germany, have a great time Leonardo😊

[@tevindavid1185]

Thanks a lot man, its 2023 and this video is the best you could get anywhere

[@mrdbourke]

Thank you Tevin! Enjoy legend!

[@LaTishaDStyles]

This is great! Very easy to follow. Just bought the course!

[@amirmatrix9134]

Dude to be honest with you you are the best one who talked about this subject like you're literally the best when you speak you just hit the spot in my brain I really wish you the best in life bro you really inspired me a lot luv ya from Iraq❤️

[@mrdbourke]

Thank you Amir! I appreciate it legend

[@floydpink469]

Very helpful for beginners ,this tutorial is the only that helped me to start with tf. If i need more, i will buy the full course. Excellent job!!.

[@Jayveersinh_Raj]

we can use tf.math.reduce_variance and tf.math.reduce_std, without .math it will throw error, and yeah these methods would not work with int, so cast them with dtype float. Btw, this is one of a kind video and channel out there, where you feel hooked, and want to learn more and more without taking rest. Knowledge is free, and to educate people with this much dedication is rare. Keep the work up :)

[@theforester_]

That's awesome Daniel, thanks for sharing. big shout out from Brazil.

[@malikhamza9286]

I am paying in thousands to my University and learning nothing but theory. Thanks to Daniel who helped me learn all this stuff for free. Thank you a lot for that.

[@muffin2426]

Your teaching style is just out of this world... wish I had a teacher like you.

[@mrdbourke]

Thank you!

[@MahipalSingh-mv3dp]

Awesome effort. Paid courses can not provide this kind of stuff. Great man.