Python-based Video Classification with Deep Learning

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Karthik K

1:11:16

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1. Fundamentals

1. Introduction.mp4

03:37

2. What is Video Classification.mp4

02:26

3. How Video Classification is done.mp4

02:03

4. About this Project.mp4

01:20

5. Why Python and Keras.mp4

02:05

6. Why Google Colab.mp4

02:20

2. Model Development and Prediction

1.1 video classification.zip

1. Download Dataset.mp4

02:47

2. What is inside the train folder and train.csv file.mp4

02:19

3. Video Classification Python Code.mp4

02:01

4. What is the .h5 file.mp4

01:25

5. What is inside the predict folder and predict.csv file.mp4

01:03

6. Enabling GPU in Google Colab.mp4

01:29

7. Is GPU connected to Colab notebook.mp4

01:56

8. Connect Google Colab with Google Drive.mp4

02:32

9. Installing TensorFlow Docs.mp4

01:44

10. Import Python Libraries.mp4

04:43

11. Training Dataset.mp4

02:07

12. Sample in train.csv.mp4

01:45

13. Label Preprocessing.mp4

03:09

14. Crop Images.mp4

02:13

15. Processing Video Frames.mp4

02:25

16. Feature Extraction.mp4

03:25

17. Data Processing.mp4

03:18

18. Building the Transformer-based Model.mp4

03:07

19. Compilation.mp4

03:36

20. Callbacks and Training.mp4

02:43

21. Visualize Model Architecture.mp4

03:17

22. Prediction.mp4

04:21

Description

Master Video Classification with Keras and Python: Build Robust Action Recognition Models from Scratch : Hands-on

What You'll Learn?

Pre-processing and cleaning of video data
Extracting features from video frames using pre-trained models
Building and training a custom Keras deep learning model for video classification
Fine-tuning a pre-trained Transformer model for video classification
Custom prediction loop for predicting actions in new videos

Who is this for?

Python developers interested in machine learning and video classification

Data scientists looking to expand their knowledge in computer vision and deep learning

Students or professionals in the field of computer science and engineering interested in developing and deploying video classification models

Anyone interested in learning how to implement a state-of-the-art video classification model using Keras and TensorFlow.

More details

Description
This course is designed to teach you how to build a video classification model using Keras and TensorFlow, with a focus on action recognition. Video classification has numerous applications, from surveillance to entertainment, making it an essential skill in today's data-driven world. Through this course, you will learn how to extract features from video frames using pre-trained convolutional neural networks, preprocess the video data for use in a custom prediction loop, and train a Transformer-based classification model using Keras.
By the end of this course, you will be able to build your own video classification model and apply it to various real-world scenarios. You will gain a deep understanding of deep learning techniques, including feature extraction, preprocessing, and training with Keras and TensorFlow. Additionally, you will learn how to optimize and fine-tune your model for better accuracy.
This course is suitable for anyone interested in deep learning and video classification, including data scientists, machine learning engineers, and computer vision experts. The demand for professionals skilled in deep learning and video classification is increasing rapidly in the industry, and this course will equip you with the necessary skills to stay ahead of the competition.
Join us today and take the first step towards becoming an expert in video classification using Keras and TensorFlow!
Who this course is for:
Python developers interested in machine learning and video classification
Data scientists looking to expand their knowledge in computer vision and deep learning
Students or professionals in the field of computer science and engineering interested in developing and deploying video classification models
Anyone interested in learning how to implement a state-of-the-art video classification model using Keras and TensorFlow.

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Engineer dedicated to utilizing the power of Machine learning and Deep learning to solve real-world problems, improve design and performance assessment. Over ten years of experience in engineering and R&D environment. Engineering professional with a focus on Multi-physics CFD-ML from IIT Madras. Experienced in implementing action-oriented solutions to complex business problem.

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