Python-based Video Classification with Deep Learning

Python-based Video Classification with Deep Learning, available at $22.99, has an average rating of 4, with 28 lectures, based on 10 reviews, and has 1039 subscribers.

You will learn about 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 This course is ideal for individuals who are Python developers interested in machine learning and video classification or Data scientists looking to expand their knowledge in computer vision and deep learning or Students or professionals in the field of computer science and engineering interested in developing and deploying video classification models or Anyone interested in learning how to implement a state-of-the-art video classification model using Keras and TensorFlow. It is particularly useful for Python developers interested in machine learning and video classification or Data scientists looking to expand their knowledge in computer vision and deep learning or Students or professionals in the field of computer science and engineering interested in developing and deploying video classification models or Anyone interested in learning how to implement a state-of-the-art video classification model using Keras and TensorFlow.

Enroll now: Python-based Video Classification with Deep Learning

Summary

Title: Python-based Video Classification with Deep Learning

Price: $22.99

Average Rating: 4

Number of Lectures: 28

Number of Published Lectures: 28

Number of Curriculum Items: 28

Number of Published Curriculum Objects: 28

Original Price: ?799

Quality Status: approved

Status: Live

What You Will 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 Should Attend

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.

Target Audiences

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.

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!

Course Curriculum

Chapter 1: Fundamentals

Lecture 1: Introduction

Lecture 2: What is Video Classification?

Lecture 3: How Video Classification is done?

Lecture 4: About this Project

Lecture 5: Why Python and Keras?

Lecture 6: Why Google Colab?

Chapter 2: Model Development and Prediction

Lecture 1: Download Dataset

Lecture 2: What is inside the train folder and train.csv file?

Lecture 3: Video Classification Python Code

Lecture 4: What is the .h5 file?

Lecture 5: What is inside the “predict” folder and “predict.csv” file?

Lecture 6: Enabling GPU in Google Colab

Lecture 7: Is GPU connected to Colab notebook?

Lecture 8: Connect Google Colab with Google Drive

Lecture 9: Installing TensorFlow Docs

Lecture 10: Import Python Libraries

Lecture 11: Training Dataset

Lecture 12: Sample in train.csv

Lecture 13: Label Preprocessing

Lecture 14: Crop Images

Lecture 15: Processing Video Frames

Lecture 16: Feature Extraction

Lecture 17: Data Processing

Lecture 18: Building the Transformer-based Model

Lecture 19: Compilation

Lecture 20: Callbacks and Training

Lecture 21: Visualize Model Architecture

Lecture 22: Prediction

Instructors

Karthik Karunakaran, Ph.D.
Transforming Real-World Problems with the Power of AI-ML

Rating Distribution

1 stars: 1 votes

2 stars: 0 votes

3 stars: 2 votes

4 stars: 2 votes

5 stars: 5 votes

Frequently Asked Questions

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