Object Detection with Tensorflow | Practical oriented with real time dataset form Scratch
From Beginner Level to Advanced Level | Completely Practical Oriented | 100% NO Coding background is required to learn this course.
Updated on Sep, 2023
Language - English
Course Description
Machine learning is an exponential technology from IBM Watson, SIRI, self driving car which are taking on the world and artificial neural network is heart of it. Object Detection is an essential technique for artificial visualization in Robotics, AI Sensory tools and many more. But the problem is Object detection with your own dataset is simply not taught at university.
So where do you learn them?
Well, online training is good option, and that's why we had a look at some of the Tensorflow object detection courses available online right now and what we found was that you all have solid background in computer science or mathematics to understand what's going on and none of the course was robust in structure. That's why we developed fully practical oriented course where non technical person can also train the tensorflow model. With your own dataset, This course will help you to detect your own object from the surroundings.
Watch this excellent preview and Demo video of the course using below link
The first thing I have focused on is a robust structure navigating a complex topic with training your own dataset. This course won't required any coding background. All types of students can learn this course. Anyone can change their existing domain with computer vision.
The course is broken down into practical sections like,
- Tensorflow introduction to latest framework 2021
- Tensorflow CPU installation with anaconda
- Tensorflow GPU installation with NVIDIA Toolkit and CUDNN library (optional)
- Dataset preparation using Kaggle's dataset or custom dataset
- Image annotation to perform faster RCNN algorithm
- Conversion to TFRECORD for input pipeline
- Training your own model with tensor board visualization
- Deployment of your trained model on Android application, web application and Realtime application
At the end of the course students will be able to detect any object from surroundings i.e. Dataset preparation to Training you own model. We are extremely passionate about bringing Machine learning to everybody on this planet and today we need your support to make this dream in reality.
Start a career path in Machine learning and enroll today. I will see you inside the course.
Goals
What will you learn in this course:
- Learn Python / Anaconda Usage.
- Learn to Prepare Opensource and Custom Dataset.
- Learn to install Tensorflow Framework.
- Learn Image annotation and Image Labelling.
- Learn to Train the ML Model.
- Learn to Visualize the trained model on Tensorboard - Graphs, Histogram.
- Learn to Deploy model on Android sample, Webserver, Webcam and Video analysis.
Prerequisites
What are the prerequisites for this course?
- Laptop or Desktop
- NVIDIA Graphic Card (Optional)
- No programming experience needed. You will learn everything that you need to know.
- This course is for all students (Technical and Non Technical).
- Spoon feeding course.
Curriculum
Check out the detailed breakdown of what’s inside the course
Course Preview
1 Lectures
-
Course Demo
02:16
02:16
Introduction to the roadmap of course
1 Lectures
Tensorflow Installation
2 Lectures
Tensorflow Framework Installation
1 Lectures
Dataset Preparation, Labelling / Annotations & Dataset Conversion
2 Lectures
Training and Deployment (Webserver, Webcam, Video Feed, Android)
3 Lectures
Instructor Details
Aakash Jadhav
Machine Learning Developer“Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the web. It would understand exactly what you wanted, and it would give you the right thing. We’re nowhere near doing that now. However, we can get incrementally closer to that, and that is basically what we work on.”
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