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

You’ve made it to part 2 of the longest code-first learn TensorFlow and deep learning fundamentals video series on YouTube!

This part continues right where part one left off so get that Google Colab window open and get ready to write plenty more TensorFlow code.

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Timestamps:
0:00 - Intro/hello/have you watched part 1? If not, you should
0:55 - 66. Non-linearity part 1 (straight lines and non-straight lines)
10:33 - 67. Non-linearity part 2 (building our first neural network with a non-linear activation function)
16:21 - 68. Non-linearity part 3 (upgrading our non-linear model with more layers)
26:40 - 69. Non-linearity part 4 (modelling our non-linear data)
35:18 - 70. Non-linearity part 5 (reproducing our non-linear functions from scratch)
49:45 - 71. Getting great results in less time by tweaking the learning rate
1:04:32 - 72. Using the history object to plot a model’s loss curves
1:10:43 - 73. Using callbacks to find a model’s ideal learning rate
1:28:16 - 74. Training and evaluating a model with an ideal learning rate
1:37:37 - [Keynote] 75. Introducing more classification methods
1:43:41 - 76. Finding the accuracy of our model
1:47:59 - 77. Creating our first confusion matrix
1:56:27 - 78. Making our confusion matrix prettier
2:10:28 - 79. Multi-class classification part 1 (preparing data)
2:21:04 - 80. Multi-class classification part 2 (becoming one with the data)
2:28:13 - 81. Multi-class classification part 3 (building a multi-class model)
2:43:52 - 82. Multi-class classification part 4 (improving our multi-class model)
2:56:35 - 83. Multi-class classification part 5 (normalised vs non-normalised)
3:00:48 - 84. Multi-class classification part 6 (finding the ideal learning rate)
3:11:27 - 85. Multi-class classification part 7 (evaluating our model)
3:25:34 - 86. Multi-class classification part 8 (creating a confusion matrix)
3:30:00 - 87. Multi-class classification part 9 (visualising random samples)
3:40:42 - 88. What patterns is our model learning?

#tensorflow #deeplearning #machinelearning

[kushalacharya]

The best part about Daniel's teaching is that he doesn't make his students feel like they are alone in their learning and becomes their companion by showing them how he would himself figure things out. This gives tremendous hope and confidence especially to the students who are just starting out in this field which is vast and ever-growing. Great job mate. You rock!!!

[subhadeepchatterjee]

I am gonna be totally honest with you, these were the most productive 14 hours of my life, Thanks Daniel for being an excellent teacher : )

[sesshomarudogdemon]

Just wanted to say thank you for working hard on providing us with all these deep and informative videos on TensorFlow and Deep Learning.

[paulntalo]

It's been an amazing tensorflow learning for the last two weeks to code along part 1 and 2 tutorial videos with ease. Thank you so much Daniel

[subhabratanath]

Can't give you enough thanks sir, I will remember these two videos for a long time because I start my deep learning journey from here.
And I think now I have a good habit to write code as much as I can rather than copying. Thank you very much sir for your effort.
Love from Kolkata(India).

[bipin_the_great]

Thank you Daniel. The course syllabus is great but most importantly the way you teach is amazing and your voice is so sweet and balanced. It is like step by step guidance and every machine learning beginners must watch this series.

[mahletalem]

Hey Daniel, I couldn't thank you enough for getting me started with TF. I am so grateful for all the work you put into the creation of your videos. Maybe, hopefully, someday I'll get to pay it forward. Thank you!

[mrdbourke]

Friends, here are some helpful links:



Happy Machine Learning!

[danish]

Just finished the 14 hours course ! Thankyou for making such a awesome tutorial Daniel.

[darshankd]

Ohh! the style of teaching . Daniel you are the best tutor for ML

[sunnymoon]

If you want to learn deep learning with hands on coding this is one of the best course !

[eidmone]

After two weeks, I finally finished the whole course! It was a great tutorial Daniel, keep up the good work!!

[GoredGored]

Thank you Daniel. I plotted accuracy per learning rate instead. Also I extracted the dataframe (history.history) index value where accuracy is the maximum. I then filtered the whole row using the iloc method. That gives me the best learning rate for the maximum accuracy. After that I just used that learning rate, build a new model and now I am getting higher accuracy even after 10 epochs (some where in the 90s).
And I am following your typing away for every new model instead of what I used to do, copy-paste and modify. Now I make a simple mistake I delete the whole thing and start again.
You completely demystified the whole thing for me and great way of teaching. Thank you again.

[sachingavande]

Hey,

I am mechanical engineer and I had fear of coding as I saw your video, I can overcome that fear, thank you so much for that.
You had explained very well, thank you so much for great session.

[Hellowow]

Best tutorial of tensorflow (part 1 and 2) on YouTube 😇👌

[ricardofigueiredo]

Daniel I finished your 14 hours right now. thank you a lot for your training videos i think it was the most engaging learning I've ever had, I could learn a little deep what is behind the scenes of machine learning and deep learning, and know how to work with tensors... i'm follow you on Linkedin... I'm happy to have this first start with you one think i will keep remembering how brought me to this world... thank you thank you thank you, cant thank you more.... see you

[roypearlmusic]

One of the best (if not THE...) courses I found on youtube. I'm definitely gonna take the whole course. Well done! and thanks man for this great material 🙏🏾

[Ayesha-wfsy]

I have just completed this course. It's just amazing. I luckily found this amazing content on youtube which I really need as I am going to start my final year project. Thanks for all this

[jyvfbnn]

Great instructor, beautifully put together. I went on and registered for the full course in ZTM and I am watching everything from the beginning again.

[PokemGaming]

Thank you so much, Daniel.
I just finished the 14 hours course for a month with 1 hour daily.