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.
✏️ Kylie Ying developed this course. Check out her channel: https://www.youtube.com/c/YCubed
⭐️ Code and Resources ⭐️
🔗 Supervised learning (classification/MAGIC): https://colab.research.google.com/drive/16w3TDn_tAku17mum98EWTmjaLHAJcsk0?usp=sharing
🔗 Supervised learning (regression/bikes): https://colab.research.google.com/drive/1m3oQ9b0oYOT-DXEy0JCdgWPLGllHMb4V?usp=sharing
🔗 Unsupervised learning (seeds): https://colab.research.google.com/drive/1zw_6ZnFPCCh6mWDAd_VBMZB4VkC3ys2q?usp=sharing
🔗 Dataets (add a note that for the bikes dataset, they may have to open the downloaded csv file and remove special characters)
🔗 MAGIC dataset: https://archive.ics.uci.edu/ml/datasets/MAGIC+Gamma+Telescope
🔗 Bikes dataset: https://archive.ics.uci.edu/ml/datasets/Seoul+Bike+Sharing+Demand
🔗 Seeds/wheat dataset: https://archive.ics.uci.edu/ml/datasets/seeds
🏗 Google provided a grant to make this course possible.
❤️ Support for this channel comes from our friends at Scrimba – the coding platform that’s reinvented interactive learning: https://scrimba.com/freecodecamp
⭐️ 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
—
Learn to code for free and get a developer job: https://www.freecodecamp.org
Read hundreds of articles on programming: https://freecodecamp.org/news
source
50 Comments
@СтепанШибряев · October 14, 2026 at 4:52 pm
williams %r plus price action sounds like a solid combo for filtering these entries
@GaiaTechWriters · October 14, 2026 at 4:52 pm
October 5th 2026. 30 MIN per day.
@MrClean520 · October 14, 2026 at 4:52 pm
Hi, I am learning this in 2026! I have a question on the last part related to PCA code. In PCA, we assume reducing 7 dimensions to 2, then fit_transform(X) to get the transformed_x. Before we draw the scatter plot, shouldn't we do the Kmeans.fit() again on the transformed_x? The kmeans.labels still contains the old classes that we got from the 7 dimensions K Means Clustering.
@nr7507 · October 14, 2026 at 4:52 pm
at ~27:00 when you talk about using the validation set to tune hyperparameters and use the model that shows the lowest loss, do you train the model again based on the adjusted hyperparameters or just apply on validation set and check the loss?
@SizaBantu54321 · October 14, 2026 at 4:52 pm
This lady is a genius
@Vielenx · October 14, 2026 at 4:52 pm
3:12 start from here
@barbaraleimstone6047 · October 14, 2026 at 4:52 pm
Thank you for this incredibly informative deep dive into what sulfate-free actually means, you always explain the chemistry so perfectly! I was definitely one of those people who blindly followed the trend without understanding the science, but once I realized how much harsh detergents were stripping my natural oils and exacerbating my hair thinning, I had to make a permanent switch. I have been using Bioonz Shampoo for a few months now precisely because it uses gentle cleansers without any SLS or parabens, which doesn't aggravate my scalp, while still removing product buildup effectively. The formula includes biotin, keratin, and argan oil, which has been crucial for my anti-hair loss routine and supporting new regrowth without drying out my ends. I really appreciate how you highlighted that the whole formula matters, not just the absence of one ingredient. Do you think that people with very hard water at home need to take extra steps when using natural cleansers to avoid mineral buildup?
@АндрейСтрулистов · October 14, 2026 at 4:52 pm
going short after breaking the lower band made so much sense
@greenwd49 · October 14, 2026 at 4:52 pm
Don't waste your time. Absolutely awful. Essentially you're watching the girl type python code
@ДамирКароннов · October 14, 2026 at 4:52 pm
с 52 до 90 за пять минут это не открытие кейсов а финансовый гений, поздравляю
@KrishnaSashank-s5i · October 14, 2026 at 4:52 pm
Helped me so much
@ThiDucPhan-l3x · October 14, 2026 at 4:52 pm
феннек фокс и файр серпент в одном заходе это просто какая-то фантастика
@AbdulWahab-qn3pj · October 14, 2026 at 4:52 pm
13:10 definately not outdated but more logical
@krishnamohan6130 · October 14, 2026 at 4:52 pm
Just happened to revise quickly my ML. While going through,
I noticed in the scale_dataset function that a new StandardScaler is fitted on each split rather than fitting on X_train and calling transform on valid/test. Was this done to keep the script concise for the lesson, or is there a specific reason?"
@kelet-studios · October 14, 2026 at 4:52 pm
I have AI olympiad rn, and it end in 2 hours. starting to learn right now
@jariuspierre-toussaint6998 · October 14, 2026 at 4:52 pm
As soon as I got here the comment section told me the grading scale here was NO JOKE.
I'm ready though, let's do it.
@Sim-z6v · October 14, 2026 at 4:52 pm
Why is Machine Learning for everyone 😂?
@bhaskar_mbn · October 14, 2026 at 4:52 pm
Thanks mam for free course
@EimonKyaw-po7yi · October 14, 2026 at 4:52 pm
Very clear explanation. Thanks
@Cloveslearning · October 14, 2026 at 4:52 pm
Such an awesome video!!! Yes, you might need to be already familiar with pandas, numpy, and some statistics, but beyond that, this is one of the most valuable courses in machine learning!! The math is clearly and simply explained and demonstrated, and the fact that she implements the code right after the explanation is so helpful!! I was already familiar with most concepts, but she helped me get a clearer picture.
@votam1144 · October 14, 2026 at 4:52 pm
Thanks you so much!
@alirezag_builds · October 14, 2026 at 4:52 pm
Thank you Kylie! you are a genius. I learned alot!
@Whatmattersus · October 14, 2026 at 4:52 pm
I finished the tutorial in two months and 2 weeks
@lucidcar2365 · October 14, 2026 at 4:52 pm
She is talking like its not for everybody.
@minhnguyen2960 · October 14, 2026 at 4:52 pm
I can actually see why Cheonsirok uses the life-manual metaphor. It’s pretty easy to picture.
@54subhodeepmaity88 · October 14, 2026 at 4:52 pm
It's really really helpful for everyone who has aspirations in machine learning. Don't chase 10hr tutorial courses. Have some theoretical knowledge and concepts and then dive into this
@nimcaanbashiir607 · October 14, 2026 at 4:52 pm
can we have the slides for this video
@The.Voidest · October 14, 2026 at 4:52 pm
20:55 10 pregnancies…. Age 29…. 😭🥀
@anilkumar-m3c1c · October 14, 2026 at 4:52 pm
we need Gen AI full Course
@gerryparque · October 14, 2026 at 4:52 pm
https://youtu.be/i_LwzRVP7bg?t=1927
@2morogamer112 · October 14, 2026 at 4:52 pm
mam 1 request please dont teach anyone each word from your create a mess so please just do whtever u want but please dont teach people if i compare u to my college professers they are far batter though they dont even have a degree……
@Baddmann1931 · October 14, 2026 at 4:52 pm
Just start a video with a disclaimer to the precursor for the series.
@KitKatKaz-h3x · October 14, 2026 at 4:52 pm
13:00 what?????
@Kingsingh-sh9el · October 14, 2026 at 4:52 pm
30:12
@ProductiveMuslimah-i4d6o · October 14, 2026 at 4:52 pm
Can I do these with my phone
@Aansh-d7s · October 14, 2026 at 4:52 pm
import csv file 3:46
@niranjanadvanture · October 14, 2026 at 4:52 pm
i think it could be a good course
@dhruvjindal682 · October 14, 2026 at 4:52 pm
What are the pre requisites for this course for an absolute beginner please tell me
@itslannem5678 · October 14, 2026 at 4:52 pm
The code and resources links are not working
@ClassicFit-i5w · October 14, 2026 at 4:52 pm
love you form India
@ข่าวยุทธศาสตร์ · October 14, 2026 at 4:52 pm
Xe điện VinFast
@ArTamaMix · October 14, 2026 at 4:52 pm
Is it necessary to change voice ? So irritating!
@MaicoFreitas-qt8fc · October 14, 2026 at 4:52 pm
33:28
The area under the density is the probability, not the y label itself
@Th0Fan · October 14, 2026 at 4:52 pm
how is this for everybody? I am one of the everybody and had no idea about ML. Very hard to understand for beginners. But seems like a good knowledge transfer
@AdeepReddy-c3g7h · October 14, 2026 at 4:52 pm
"For every body" on the video thumbnail hit hard in 5 minutes
@Ambitionincarn8 · October 14, 2026 at 4:52 pm
Bored, legit have no clue what this is, but somehow i’m here. Interesting.
@НикитаЗимкин · October 14, 2026 at 4:52 pm
from 90 bucks to over a grand is just pure skill honestly😃
@jaldesai3950 · October 14, 2026 at 4:52 pm
Kylie ying , your teaching is worst i don't recommend this video to anyone
@СтефанТекарев · October 14, 2026 at 4:52 pm
финал просто эпический ради таких моментов и смотрим
@chaaiandcode · October 14, 2026 at 4:52 pm
now i want to become like her! even more!!