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sister may i know when will your source start as It will so help full for my first year at collage

I just completed my undergraduation last month and I have very good experience in Machine Learning but one thing is missing in my life that is those fun memories in my life and after watching your video I realized that I have missed so many things. I am coming to the USA for MS in Artificial Intelligence and I hope that along with academic things I'll enjoy my life to the fullest and make those 2 years, the best 2 years of my life (I promise this to myself).

One day , I will do this vidéo for me

Inspiring! ✨✨

Machine Learning = Robot consciousnes, (but not awareness)

you don't understand how much I love this girl

You are such a great teacher. I'm just glad to know such teachers exist. I would love talk to you someday!

Hi can you please recommend some youyube channel you like it and good for us please?

2nd error found in the code: InvalidArgument: 400 The requested language is not supported by models/text-bison-001

bahut sohna boldi a kamliye

This is amazing Kylie! I was just thinking of finding a way to summarize google reviews. I think something to take this a step further is to show the pros, cons, what's the most ordered/mentioned dishes, what dishes people didn't like

Amazing!

You looks chinese origin, So ofc you guys are born genius. May god more bless people like you and China

make a video on the best resources to learn all the concept of machine learning it might be a hard copy or a soft copy

Kylie - Your course content is excellent. Thank you for sharing.

Waiting ❤

You are too cute 🥰 teacher 😻💞 Love you Teaching MAM

Very helpful! Thank you

mine didnt work

This video was execellent

I need help ive just finished my python and two pandas and numpy librebries, the thing is i want to learn matchin learning and now i have watched so many are suggesting different different kind of Libs and things and that's making me confusing and not available the courses of Libs of those they suggest and now im confused that what to learn and where to take next move for ML

99% of the content that provides road maps for beginners does not mention the importance of the foundation in programming, such as algorithms, data structures, and database, which is considered one of the basics for every technological path. Therefore, everyone fails to complete the path they started with because they do not know the basics.

From which country you belong to,? And congratulations 🎉. I really wanted to get into MIT it's a very different feeling ❤.

i didnt get Selenium

🥰😃

Thank you for the video! I'm currently using the dining room table as a "workstation". In due time, I'll have a legit setup 🙏

your video filled a new energy for me ❤❤❤❤

Nice vid and JESUS WANTS YOU IN HEAVEN

this is really clear explanation

looking forward to more from this machine learning series...

congratulations, after watching this video I submitted an application to MIT for a full scholarship.just learned that IHTFP is MIT haha

That's a great one. Thankyou :)

Only 5 years I thought you have extention programs. Food supplies.

Kylie Do you box? 🥊, I saw the stationary ground bag thing in the back.

I like to apply for things I’m not particularly experienced in, but around by proxy. This should help 😎

The end of the video states it would make Kylie’s day if I smash the subscribe button ( did years ago as one of her videos saved me a ton of time in AI and clicked the notification bell I think) but if I’m back here to make Kylie’s night, I should smash…?🗿

What computer would you recommend PC or Mac? Air or Pro. if Mac? What specs? Thank you.

Good job Kylie! Note: You don't need to cal the parent class's __init__ from the child class's __init__ if the child doesn't introduce any new attributes

you can give us an entire series of Python vid, it will be useful for all the datageeks, who want to learn form the best of the best

How long should this take from start to finish

Foundational math: probability and statistics, calculus, linear algebra The first thing you need to do is lay down a good foundation in math. This includes probability and statistics, calculus, and linear algebra. Probability and statistics are important because machine learning is all about making predictions. You need to understand things like conditional probability, base rule, and statistical distributions. Calculus is helpful because a lot of machine learning is about optimization problems. Gradient descent, a common optimization algorithm, is based on calculus. Linear algebra is necessary because machine learning models often involve a lot of data and computations. Linear algebra helps you solve these problems more efficiently. Once you have a foundation in math, you can start learning about the core concepts of machine learning. These include: Core concepts: convolutional neural networks (CNNs), recurrent neural networks (RNNs), LSTMs Training and evaluating a model: metrics, overfitting Finally, you need to practice and gain more expertise in machine learning. Here are some tips: Do projects online to learn how other people do machine learning. Use the UCI machine learning repository to practice building simple models. Participate in Kaggle competitions to learn from other people and see what they are doing. Read research papers and try to implement them yourself.

thanks for roadmap

Smart, beautiful creator, good public speaking, thank you for providing good information. underrated creators❤

Just watched your video on leaving MIT, and it made me cry.. truly inspirational, and I’ve come to be your follower for the rest of my life.. and thank you for your amazing content

Excellent madam

thx a lot Kylie 🤗🤗🤗

La invito a estudiar la carrera de la vida

Can we complete the roadmap and make 1 or 2 project in 1 month?

lol

Actually this video is very insiring and gives me the opportunity to rethink about my future moves once again cause' MIT has always been a special place in my heart. In the near future I as well will be where i belong. #highqualitycontent