Quantum Data Analytics
Quantum Data Analytics
  • Видео 214
  • Просмотров 3 811
29. Gaussian Mixture Model (GMM) in machine learning
Welcome to this in-depth tutorial on the Gaussian Mixture Model (GMM) in machine learning!
In this video, we explore the GMM model, a powerful probabilistic model used for clustering and density estimation. GMM is based on a mixture of multiple Gaussian distributions, each representing a different cluster or component in the data. We’ll dive into the mathematical foundation of GMMs, how they can be implemented using popular machine learning libraries, and real-world applications where GMMs shine.
You’ll learn:
What is a Gaussian Mixture Model?
How does GMM work for clustering and anomaly detection?
Key algorithms such as Expectation-Maximization (EM) for fitting GMM to data.
How to implement GM...
Просмотров: 10

Видео

28. DBSCAN (Density-Based Spatial Clustering of Applications with Noise) Explained6:2028. DBSCAN (Density-Based Spatial Clustering of Applications with Noise) Explained
28. DBSCAN (Density-Based Spatial Clustering of Applications with Noise) Explained
Просмотров 244 часа назад
DBSCAN (Density-Based Spatial Clustering of Applications with Noise) Explained | Machine Learning Tutorial In this video, we dive deep into DBSCAN, a popular clustering algorithm in machine learning. Learn how DBSCAN groups data points based on their density, making it an excellent choice for datasets with noise or outliers. We'll explore: What DBSCAN is and how it works Key parameters: epsilon...
27. Understanding Silhouette Score in Machine Learning | What is Silhouette Score?5:0327. Understanding Silhouette Score in Machine Learning | What is Silhouette Score?
27. Understanding Silhouette Score in Machine Learning | What is Silhouette Score?
Просмотров 119 часов назад
In this video, we dive deep into the concept of Silhouette Score in machine learning. The Silhouette Score is a powerful metric used to evaluate the quality of clustering in unsupervised learning algorithms like K-Means and DBSCAN. It helps assess how well-defined and distinct the clusters are by measuring both cohesion (how close the points within a cluster are) and separation (how distinct di...
26. Understanding K-Means Algorithm in Machine Learning5:1726. Understanding K-Means Algorithm in Machine Learning
26. Understanding K-Means Algorithm in Machine Learning
Просмотров 11512 часов назад
In this video, we dive deep into the K-Means algorithm, one of the most widely used clustering techniques in machine learning. Whether you're a beginner or looking to refresh your understanding, this video will explain how K-Means works, its key concepts, and how to implement it in Python. 🔍 What you'll learn in this video: What is the K-Means clustering algorithm? How does the K-Means algorith...
25. Locally Linear Embedding (LLE)7:0625. Locally Linear Embedding (LLE)
25. Locally Linear Embedding (LLE)
Просмотров 2714 часов назад
Welcome to this detailed exploration of Locally Linear Embedding (LLE) in Machine Learning! In this video, we dive deep into this powerful dimensionality reduction technique and how it can be used to uncover hidden patterns in high-dimensional data. You will learn: - What LLE is and why it's a popular choice for nonlinear dimensionality reduction. - How LLE preserves local structures while redu...
24. Bias and Variance Tradeoff Explained6:4024. Bias and Variance Tradeoff Explained
24. Bias and Variance Tradeoff Explained
Просмотров 116 часов назад
In this video, we dive into the fundamental concept of the Bias-Variance Tradeoff, a critical idea in machine learning and statistical modeling. We explore how the balance between bias (the error introduced by approximating a real-world problem with a simplified model) and variance (the error introduced by the model's sensitivity to small fluctuations in the training data) affects the performan...
23. Understanding Random Projection in Machine Learning6:4723. Understanding Random Projection in Machine Learning
23. Understanding Random Projection in Machine Learning
Просмотров 2119 часов назад
Welcome to our channel! In today's video, we will dive into Random Projection-a fascinating dimensionality reduction technique used in machine learning. If you've ever worked with high-dimensional data, you know that managing and processing it can be computationally expensive and time-consuming. That's where random projection comes in! We'll explore the theory behind random projection, how it w...
22.Introduction to Principal Component Analysis (PCA) in Machine Learning7:4122.Introduction to Principal Component Analysis (PCA) in Machine Learning
22.Introduction to Principal Component Analysis (PCA) in Machine Learning
Просмотров 921 час назад
22.Introduction to Principal Component Analysis (PCA) in Machine Learning
21.Mastering Stacking in Machine Learning: Boost Your Model's Performance!5:1221.Mastering Stacking in Machine Learning: Boost Your Model's Performance!
21.Mastering Stacking in Machine Learning: Boost Your Model's Performance!
Просмотров 10День назад
21.Mastering Stacking in Machine Learning: Boost Your Model's Performance!
20. Understanding Gradient Boosting: A Powerful Machine Learning Technique7:2420. Understanding Gradient Boosting: A Powerful Machine Learning Technique
20. Understanding Gradient Boosting: A Powerful Machine Learning Technique
Просмотров 34День назад
20. Understanding Gradient Boosting: A Powerful Machine Learning Technique
19. Understanding AdaBoost Algorithm | Machine Learning Explained8:2919. Understanding AdaBoost Algorithm | Machine Learning Explained
19. Understanding AdaBoost Algorithm | Machine Learning Explained
Просмотров 142День назад
19. Understanding AdaBoost Algorithm | Machine Learning Explained
18. Understanding Random Forest: A Comprehensive Guide7:4818. Understanding Random Forest: A Comprehensive Guide
18. Understanding Random Forest: A Comprehensive Guide
Просмотров 18День назад
18. Understanding Random Forest: A Comprehensive Guide
17. Bagging and Pasting| Machine Learning7:1817. Bagging and Pasting| Machine Learning
17. Bagging and Pasting| Machine Learning
Просмотров 1914 дней назад
17. Bagging and Pasting| Machine Learning
16. Voting Classifier Explained | Machine Learning5:3916. Voting Classifier Explained | Machine Learning
16. Voting Classifier Explained | Machine Learning
Просмотров 614 дней назад
16. Voting Classifier Explained | Machine Learning
15. Understanding Decision Trees | Machine Learning Explained6:0815. Understanding Decision Trees | Machine Learning Explained
15. Understanding Decision Trees | Machine Learning Explained
Просмотров 1114 дней назад
15. Understanding Decision Trees | Machine Learning Explained
14. SVM Regression Explained7:4614. SVM Regression Explained
14. SVM Regression Explained
Просмотров 1814 дней назад
14. SVM Regression Explained
13. Mastering SVM: The Ultimate Guide to Support Vector Machines6:0513. Mastering SVM: The Ultimate Guide to Support Vector Machines
13. Mastering SVM: The Ultimate Guide to Support Vector Machines
Просмотров 8514 дней назад
13. Mastering SVM: The Ultimate Guide to Support Vector Machines
12. Softmax Regression6:2612. Softmax Regression
12. Softmax Regression
Просмотров 2721 день назад
12. Softmax Regression
11. Understanding Logistic Regression - A Comprehensive Guide7:4911. Understanding Logistic Regression - A Comprehensive Guide
11. Understanding Logistic Regression - A Comprehensive Guide
Просмотров 5121 день назад
11. Understanding Logistic Regression - A Comprehensive Guide
10. Elastic Net Regression: A Comprehensive Guide5:1910. Elastic Net Regression: A Comprehensive Guide
10. Elastic Net Regression: A Comprehensive Guide
Просмотров 1321 день назад
10. Elastic Net Regression: A Comprehensive Guide
9. Lasso Regression Explained - Feature Selection & Regularization in Machine Learning4:329. Lasso Regression Explained - Feature Selection & Regularization in Machine Learning
9. Lasso Regression Explained - Feature Selection & Regularization in Machine Learning
Просмотров 2621 день назад
9. Lasso Regression Explained - Feature Selection & Regularization in Machine Learning
8. Understanding Regularization in Machine Learning | What is Regularization and Why It's Important6:168. Understanding Regularization in Machine Learning | What is Regularization and Why It's Important
8. Understanding Regularization in Machine Learning | What is Regularization and Why It's Important
Просмотров 1028 дней назад
8. Understanding Regularization in Machine Learning | What is Regularization and Why It's Important
7. Understanding the Machine Learning Learning Curve5:367. Understanding the Machine Learning Learning Curve
7. Understanding the Machine Learning Learning Curve
Просмотров 1028 дней назад
7. Understanding the Machine Learning Learning Curve
6. Polynomial Regression Explained | How to Model Non-Linear Data5:386. Polynomial Regression Explained | How to Model Non-Linear Data
6. Polynomial Regression Explained | How to Model Non-Linear Data
Просмотров 28Месяц назад
6. Polynomial Regression Explained | How to Model Non-Linear Data
5. Understanding Stochastic Gradient Descent (SGD) - A Comprehensive Guide7:025. Understanding Stochastic Gradient Descent (SGD) - A Comprehensive Guide
5. Understanding Stochastic Gradient Descent (SGD) - A Comprehensive Guide
Просмотров 59Месяц назад
5. Understanding Stochastic Gradient Descent (SGD) - A Comprehensive Guide
4. Mini-Batch Gradient Descent Explained | Machine Learning Fundamentals6:164. Mini-Batch Gradient Descent Explained | Machine Learning Fundamentals
4. Mini-Batch Gradient Descent Explained | Machine Learning Fundamentals
Просмотров 35Месяц назад
4. Mini-Batch Gradient Descent Explained | Machine Learning Fundamentals
3.Understanding Batch Gradient Descent - Machine Learning Explained7:433.Understanding Batch Gradient Descent - Machine Learning Explained
3.Understanding Batch Gradient Descent - Machine Learning Explained
Просмотров 25Месяц назад
3.Understanding Batch Gradient Descent - Machine Learning Explained
2. RMSE, MSE, and R-Squared Explained | Key Metrics for Evaluating Machine Learning Models7:022. RMSE, MSE, and R-Squared Explained | Key Metrics for Evaluating Machine Learning Models
2. RMSE, MSE, and R-Squared Explained | Key Metrics for Evaluating Machine Learning Models
Просмотров 28Месяц назад
2. RMSE, MSE, and R-Squared Explained | Key Metrics for Evaluating Machine Learning Models
1. Linear Regression8:301. Linear Regression
1. Linear Regression
Просмотров 89Месяц назад
1. Linear Regression
🌟 Top 5 LLM Models: Ratings, Pros & Cons | The Ultimate AI Showdown! 🤖✨5:45🌟 Top 5 LLM Models: Ratings, Pros & Cons | The Ultimate AI Showdown! 🤖✨
🌟 Top 5 LLM Models: Ratings, Pros & Cons | The Ultimate AI Showdown! 🤖✨
Просмотров 874 месяца назад
🌟 Top 5 LLM Models: Ratings, Pros & Cons | The Ultimate AI Showdown! 🤖✨

Комментарии

  • @brainheap
    @brainheap 7 дней назад

    C

  • @lakshaysharma6390
    @lakshaysharma6390 10 дней назад

    Thank You

  • @MariaLee-x4j
    @MariaLee-x4j 18 дней назад

    Great content, as always! Just a quick off-topic question: My OKX wallet holds some USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). Could you explain how to move them to Binance?

  • @RohanKumar-e2y
    @RohanKumar-e2y 3 месяца назад

    Option B

  • @eliastouil7686
    @eliastouil7686 3 месяца назад

    FAANG on deez nuts with your cap question

  • @br3adstix_gaming
    @br3adstix_gaming 4 месяца назад

    B

  • @praveenkumars1919
    @praveenkumars1919 4 месяца назад

    Insert

  • @user-nl4sz6nu4p
    @user-nl4sz6nu4p 4 месяца назад

    Def

  • @aziwii4052
    @aziwii4052 4 месяца назад

    Stack

  • @rumon859
    @rumon859 9 месяцев назад

    Thanks for making this video! Could you please provide code?

  • @quantum-data-analytics
    @quantum-data-analytics Год назад

    By Mistake recorded without audio.

  • @musachongan4922
    @musachongan4922 Год назад

    Great work, this is the structure format I have been looking for. I just wish the frontside was bigger and the HD format is 1080p

  • @houssembensalah7502
    @houssembensalah7502 Год назад

    first viewer and first commentator XD , I hope you get more in the future good luck !

  • @theecanmole
    @theecanmole Год назад

    I hope this comment is received as a helpful comment and not criticism. I am afraid I can't hear your audio and I can barely read your screen.