Machine Learning for Everybody – Full Course

Learn Machine Learning in a way that is accessible to absolute beginners. You will learn the basics of Machine Learning and how to use TensorFlow to implement many different concepts.

⭐️ Code and Resources ⭐️
🔗 Dataets (add a note that for the bikes dataset, they may have to open the downloaded csv file and remove special characters)

🏗 Google provided a grant to make this course possible.

⭐️ Contents ⭐️
⌨️ (0:00:00) Intro
⌨️ (0:00:58) Data/Colab Intro
⌨️ (0:08:45) Intro to Machine Learning
⌨️ (0:12:26) Features
⌨️ (0:17:23) Classification/Regression
⌨️ (0:19:57) Training Model
⌨️ (0:30:57) Preparing Data
⌨️ (0:44:43) K-Nearest Neighbors
⌨️ (0:52:42) KNN Implementation
⌨️ (1:08:43) Naive Bayes
⌨️ (1:17:30) Naive Bayes Implementation
⌨️ (1:19:22) Logistic Regression
⌨️ (1:27:56) Log Regression Implementation
⌨️ (1:29:13) Support Vector Machine
⌨️ (1:37:54) SVM Implementation
⌨️ (1:39:44) Neural Networks
⌨️ (1:47:57) Tensorflow
⌨️ (1:49:50) Classification NN using Tensorflow
⌨️ (2:10:12) Linear Regression
⌨️ (2:34:54) Lin Regression Implementation
⌨️ (2:57:44) Lin Regression using a Neuron
⌨️ (3:00:15) Regression NN using Tensorflow
⌨️ (3:13:13) K-Means Clustering
⌨️ (3:23:46) Principal Component Analysis
⌨️ (3:33:54) K-Means and PCA Implementations

🎉 Thanks to our Champion and Sponsor supporters:
👾 Raymond Odero
👾 Agustín Kussrow
👾 aldo ferretti
👾 Otis Morgan
👾 DeezMaster

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[auliamardhatillah]

Yesterday I click on a video called 'learning phyton for Beginners'. Today youtube's algorithm sent this video. I was so confuse but somehow listen to it and when I feel I understand something from this explanation, it makes me excited. A genius can make someone understand complicated things, I am very grateful.

[limwei]

I've been trying to learn ML for quite awhile but could never really grasp the algorithim. She explains how the formula comes about and why is it used in the classification or regression so well. My god. Thumbs up for sensei Kylie and free code camp!!!

[jpbaugh]

For anyone getting an error related to converting a list to a float, the model.evaluate is actually returning a list. She has the correction in the code at around 2:05:51, but she doesn't explicitly mention the correction. You just grab the first value in the list (which is why she puts [0]). So change the line where you obtain the val_loss to:

val_loss = model.evaluate(X_valid, y_valid)[0]

[Iknowpython]

⌨ (0:00:00) Intro
⌨ (0:00:58) Data/Colab Intro
⌨ (0:08:45) Intro to Machine Learning
⌨ (0:12:26) Features
⌨ (0:17:23) Classification/Regression
⌨ (0:19:57) Training Model
⌨ (0:30:57) Preparing Data
⌨ (0:44:43) K-Nearest Neighbors
⌨ (0:52:42) KNN Implementation
⌨ (1:08:43) Naive Bayes
⌨ (1:17:30) Naive Bayes Implementation
⌨ (1:19:22) Logistic Regression
⌨ (1:27:56) Log Regression Implementation
⌨ (1:29:13) Support Vector Machine
⌨ (1:37:54) SVM Implementation
⌨ (1:39:44) Neural Networks
⌨ (1:47:57) Tensorflow
⌨ (1:49:50) Classification NN using Tensorflow
⌨ (2:10:12) Linear Regression
⌨ (2:34:54) Lin Regression Implementation
⌨ (2:57:44) Lin Regression using a Neuron
⌨ (3:00:15) Regression NN using Tensorflow
⌨ (3:13:13) K-Means Clustering
⌨ (3:23:46) Principal Component Analysis
⌨ (3:33:54) K-Means and PCA Implementations

[risebyliftingothers]

Thanks for an amazingly simplified approach to ML 👍

[ibtehaj]

I have to agree with those calling this tutorial too hard. I am a professional developer studying Cyber-Sec at the Master's level and found the first hour of the tutorial to be so intimidating that I had to go and learn Python again, just to boost my confidence. I followed it by getting a tutorial on Pandas as well as Numpy, those helped.

I came back and realized that, while this is a really good tutorial, it isn't beginner-friendly at all. The kind of stuff Kylie accomplishes in a single line needs multiple lines from me and many more minutes to understand what's going on.

As advice to all the newbies, don't be intimidated, try taking the Python basics, Pandas and Numpy courses before attempting this tutorial, perhaps watch the first hour to see what's required and come back.

[jingzhang]

I just finished watching the entire video, taking a few days off to rest. Meanwhile, I also typed out all the code on Colab, mimicking what was shown. Overall, this video gave me a preliminary understanding of machine learning and opened the door to this unknown field for me. Of course, there is still a lot I need to learn, and many concepts are not very clear to me yet. However, with the prevalence of ChatGPT now, I can ask questions whenever I don't understand something. Compared to the previous technical environment, ChatGPT has made my learning process faster and more efficient. Finally, I would like to thank the blogger again. Perhaps, in the not-too-distant future, I might also make videos to guide others in getting started, haha.

[ImAnEmergency]

I have no idea how my YouTube algorithm brought me here while I was sleeping but it made for some strange dreams

[sangeethastudio]

You are literally the best, I've been looking for a tutorial for three days and yours works

[rajkadam]

This is my first Course which I've completed from FCC, got a good understanding on ML now, Thank you !!

[itskindastrange]

I recently completed the ML tutorial, and I wanted to express my gratitude for the outstanding content. The derivation and mathematical explanations were particularly impressive. I've been trying to grasp the fundamentals of machine learning for quite some time now, and this is the first tutorial where I genuinely understood the derivations and gained valuable knowledge about the topics plus the side by side implementation also helped alot. Thank you for creating such an informative and well-structured tutorial!

[christianavasa]

Absolutely brilliant. As mentioned in the intro Kylie is a true genius. god bless her

[Lodermeier]

Kylie is such a great teacher and obviously not only understands but applies these topics in the real world. What a great combination, thanks for the course!

[seeker]

Her voice and way of teaching is so soothing. I fell asleep listening to her and I am gonna watch this every night.

[harunoz]

*NichesPanel likes this xD* we all know that they isn't, but do you think models buy followers to appear on the internet?

[hutofrock]

I love it! I must say this is one of the most comprehensive and well structured videos I've watched lately! Big kudos to Kylie!

[Vlapstone]

this is perfect! By far the best I´ve found out there, such a clear and complete explanation. Great teacher.

[geld]

my 7th day - still not finished. Just so nice to see someone do ML work live! Thank you

[anushka.narsima]

Tysm for covering sooo much so quickly and it was all clear and to the point and I cant appreciate it

[ahmadF]

I just finished taking this course. I took a while. but she explains the theory and examples. I loved the math part of it. she goes on explaining the Supervised vs Unsupervised ML tools and methods. I learnt a lot also with Pyrhon. Thanks for your effort.