Machine Learning for Everybody – Full Course

It seems half of us are here after falling asleep

⌨ (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

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

falling asleep lands me in odd places

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]

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.

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

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!!!

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

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!

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

Thanks for an amazingly simplified approach to ML 👍

If you're getting an error about comparing a list to a float. Changing the "least_val_loss" variable to a list with two infinite floats will fix it. Like this: least_val_loss = [float('inf'), float('inf')]

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

Kylie Ying is a gift to humanity

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

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

Thanks for the explanations! it is really detailed, her tone is comfortable, I can easily to understand what she said and she elaborates each steps (it is so important as every self learner can know the rationale behind each steps). Hope I can watch another lesson videos of this editor!

Yes, as everyone is the audience let's start with an example that few can relate to and then just jump into code, again, everyone is well versed in code, without any explanation or overview.

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