Mastering Support Vector Machines with Python and Scikit-Learn

Описание к видео Mastering Support Vector Machines with Python and Scikit-Learn

Are you ready to delve into the world of machine learning algorithms and enhance your understanding of SVM? In this comprehensive tutorial, we'll guide you through the ins and outs of Support Vector Machines, one of the most powerful and versatile tools in the machine learning toolbox.

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: [email protected]
🌐 Website & Blog: https://ryannolandata.com/

🍿 WATCH NEXT
Scikit-Learn and Machine Learning Playlist:    • Scikit-Learn Tutorials - Master Machi...  
Random Forest Classifier:    • Random Forest Algorithm Explained wit...  
Extra Trees Classifier:    • Extra Trees Classifier in Scikit-Lear...  
Logistic Regression:    • Hands-On Machine Learning: Logistic R...  

MY OTHER SOCIALS:
👨‍💻 LinkedIn:   / ryan-p-nolan  
🐦 Twitter:   / ryannolan_  
⚙️ GitHub: https://github.com/RyanNolanData
🖥️ Discord:   / discord  

📚 *Practice SQL & Python Interview Questions: https://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 YouTube 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.

Комментарии

Информация по комментариям в разработке