PCA Analysis in Python Explained (Scikit - Learn)

Ғылым және технология

Welcome to our comprehensive guide on Principal Component Analysis (PCA). In this video, we will go over what PCA is and why it's essential in data analysis and dimensionality reduction
and How to perform PCA step-by-step with practical examples in Python.
Interested in discussing a Data or AI project? Feel free to reach out via email or simply complete the contact form on my website.
📧 Email: ryannolandata@gmail.com
🌐 Website & Blog: ryannolandata.com/
🍿 WATCH NEXT
Scikit-Learn and Machine Learning Playlist: • Scikit-Learn Tutorials...
Hyperparameter Tuning: • Hands-On Hyperparamete...
Titanic Data Science Project: • Beginner Data Science ...
Cross Validation: • A Comprehensive Guide ...
MY OTHER SOCIALS:
👨‍💻 LinkedIn: / ryan-p-nolan
🐦 Twitter: / ryannolan_
⚙️ GitHub: github.com/RyanNolanData
🖥️ Discord: / discord
📚 *Practice SQL & Python Interview Questions: stratascratch.com/?via=ryan
WHO AM I?
As a full-time data analyst/scientist at a fintech company specializing in combating fraud within underwriting and risk, I've transitioned from my background in Electrical Engineering to pursue my true passion: data. In this dynamic field, I've discovered a profound interest in leveraging data analytics to address complex challenges in the financial sector.
This KZread channel serves as both a platform for sharing knowledge and a personal journey of continuous learning. With a commitment to growth, I aim to expand my skill set by publishing 2 to 3 new videos each week, delving into various aspects of data analytics/science and Artificial Intelligence. Join me on this exciting journey as we explore the endless possibilities of data together.
*This is an affiliate program. I may receive a small portion of the final sale at no extra cost to you.

Пікірлер: 7

  • @bommijn
    @bommijnАй бұрын

    Hey, something i noticed. You copy the column names back into your X_train after scaling. Is it not easier to do "X_train = pd.DataFrame(ss.fit_transform(X_train), columns=X_train.columns)"

  • @user-iu5nz2gy6l
    @user-iu5nz2gy6l3 ай бұрын

    Thanks- another great video. But i do have 2 questions? 1) how do i retrieve the column name of the component that has the most explained variance (for EDA purposes). 2) is PCA used for feature engineering? or will you have a video that talk about feature engineering later on?

  • @alexhernandezherrera5198
    @alexhernandezherrera51982 ай бұрын

    great video, thanks for explain clearly

  • @RyanNolanData

    @RyanNolanData

    2 ай бұрын

    No problem

  • @Divy91311
    @Divy9131110 ай бұрын

    Hey Ryan , really nice video! I was wondering if I could help you edit your videos and also make a highly engaging Thumbnail which will help your video to reach to a wider audience .

  • @RyanNolanData

    @RyanNolanData

    10 ай бұрын

    Sorry have an editor and I make my own thumbnail. I appreciate you reaching out though

  • @Divy91311

    @Divy91311

    10 ай бұрын

    @@RyanNolanData Sure bro no problem, if anyone in your contact is searching for an editor please refer me !!

Келесі