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1. Building an Image Classifier with Sequential API Using Fashion MNIST Dataset
In this tutorial, we will guide you through the process of building a powerful image classifier using TensorFlow's Sequential API and the Fashion MNIST dataset. Fashion MNIST is a popular dataset of 60,000 28x28 grayscale images of 10 different fashion categories, making it an excellent starting point for training image classifiers.
We will cover the following steps:
Loading and preparing the Fashion MNIST dataset
Preprocessing the data for neural network input
Building a simple deep learning model using the Sequential API
Compiling and training the model
Evaluating the model's performance
Making predictions on new data
By the end of this video, you will have a solid understanding of how to build a neural network for image classification and be able to apply these concepts to other image recognition tasks. Whether you're a beginner or intermediate learner in deep learning, this tutorial is perfect for you!
Don't forget to like, comment, and subscribe for more tutorials on machine learning and AI!
Tools & Libraries:
TensorFlow
Keras
Fashion MNIST Dataset
#MachineLearning #DeepLearning #TensorFlow #FashionMNIST #ImageClassification #AI
Переглядів: 21

Відео

30. Gaussian Mixture Models (GMMs) for anomaly detection in Machine Learning6:3230. Gaussian Mixture Models (GMMs) for anomaly detection in Machine Learning
30. Gaussian Mixture Models (GMMs) for anomaly detection in Machine Learning
Переглядів 357 годин тому
In this video, we dive into the powerful application of Gaussian Mixture Models (GMMs) for anomaly detection in Machine Learning. We explore how GMMs can be used to model data distributions and detect outliers by identifying data points that deviate significantly from the expected patterns. You'll learn: What Gaussian Mixture Models are and how they work How GMMs are applied in anomaly detectio...
29. Gaussian Mixture Model (GMM) in machine learning7:0729. Gaussian Mixture Model (GMM) in machine learning
29. Gaussian Mixture Model (GMM) in machine learning
Переглядів 1212 годин тому
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 ca...
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
Переглядів 2714 годин тому
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?
Переглядів 2519 годин тому
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
Переглядів 12721 годину тому
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)
Переглядів 42День тому
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
Переглядів 2День тому
24. Bias and Variance Tradeoff Explained
23. Understanding Random Projection in Machine Learning6:4723. Understanding Random Projection in Machine Learning
23. Understanding Random Projection in Machine Learning
Переглядів 24День тому
23. Understanding Random Projection in Machine Learning
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
Переглядів 17День тому
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!
Переглядів 1414 днів тому
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
Переглядів 3514 днів тому
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
Переглядів 14814 днів тому
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
Переглядів 2114 днів тому
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
Переглядів 2314 днів тому
17. Bagging and Pasting| Machine Learning
16. Voting Classifier Explained | Machine Learning5:3916. Voting Classifier Explained | Machine Learning
16. Voting Classifier Explained | Machine Learning
Переглядів 814 днів тому
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
Переглядів 1314 днів тому
15. Understanding Decision Trees | Machine Learning Explained
14. SVM Regression Explained7:4614. SVM Regression Explained
14. SVM Regression Explained
Переглядів 2021 день тому
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
Переглядів 8721 день тому
13. Mastering SVM: The Ultimate Guide to Support Vector Machines
12. Softmax Regression6:2612. Softmax Regression
12. Softmax Regression
Переглядів 2921 день тому
12. Softmax Regression
11. Understanding Logistic Regression - A Comprehensive Guide7:4911. Understanding Logistic Regression - A Comprehensive Guide
11. Understanding Logistic Regression - A Comprehensive Guide
Переглядів 5321 день тому
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
Переглядів 1628 днів тому
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
Переглядів 30Місяць тому
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
Переглядів 13Місяць тому
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
Переглядів 12Місяць тому
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
Переглядів 29Місяць тому
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
Переглядів 59Місяць тому
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
Переглядів 35Місяць тому
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
Переглядів 25Місяць тому
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
Переглядів 28Місяць тому
2. RMSE, MSE, and R-Squared Explained | Key Metrics for Evaluating Machine Learning Models

КОМЕНТАРІ

  • @brainheap
    @brainheap 11 днів тому

    C

  • @lakshaysharma6390
    @lakshaysharma6390 14 днів тому

    Thank You

  • @MariaLee-x4j
    @MariaLee-x4j 22 дні тому

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  • @RohanKumar-e2y
    @RohanKumar-e2y 4 місяці тому

    Option B

  • @eliastouil7686
    @eliastouil7686 4 місяці тому

    FAANG on deez nuts with your cap question

  • @br3adstix_gaming
    @br3adstix_gaming 4 місяці тому

    B

  • @praveenkumars1919
    @praveenkumars1919 4 місяці тому

    Insert

  • @user-nl4sz6nu4p
    @user-nl4sz6nu4p 4 місяці тому

    Def

  • @aziwii4052
    @aziwii4052 4 місяці тому

    Stack

  • @rumon859
    @rumon859 9 місяців тому

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

  • @quantum-data-analytics
    @quantum-data-analytics Рік тому

    By Mistake recorded without audio.

  • @musachongan4922
    @musachongan4922 Рік тому

    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 Рік тому

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

  • @theecanmole
    @theecanmole Рік тому

    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.