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Udemy - Data Science - Deep Learning Project For Self Driving Cars
TORRENT SUMMARY
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Introduction to the Google Colab and Importing necessary Libraries
Cloning , Exploring and Visualize Datasets
Image pre-processing that includes Grayscale conversion , Applying Histogram Equalization Technique and Image Normalization
Building Convolutional Neural Networks with Keras
Compile and Train a Deep Learning Model that can identify between 43 different Traffic Signs
Test model with the test dataset & oversee the performance of trained convolution neural network model
Requirements
Basic Python Programming
Basics of Neural Network
Description
This is a Hands-on Project. You learn by Practice.
No unnecessary lectures. No unnecessary details
.
A precise, to the point and efficient course
made for those who want to learn the most important part of Data Science
Importing Datasets, Building Models using the Datasets and Training and Testing the Models. Everything else revolves around this.
Although, for the sake of this project we will using traffic signs for autonomous vehicles to learn about Deep Learning and Data Science. The same process can be repeated for other projects too. The same process and techniques can be repeated for other Deep learning projects. Some such projects that you can build following similar process are
Self Driving Cars (This project)
Skin Cancer Detection
Currency Detection
Human Facial Recognition
You will learn
more
in this
one hour of Practice
that hundreds of hours of unnecessary theoretical lectures.
Data Science is the hottest job of the 21st century. You need good programming skills and analytical skills and years of hard work to be a Pro in Data science. This one hour course is precise , to the point and efficient . It has no unnecessary details.
This is the only course you need
.We understand our students are Professionals and have limited time and limited attention span. Taking a few months course and forgetting everything along the way is not a efficient way to lean. We learn by practice.
Learn the most important aspect of Data Science :
Importing and working with Datasets
Building a Deep Convolutional Network Model using Keras
Compile, train, test and analyze the model
We will build a Traffic Sign Classifier using Keras. In this hands-on project, we will complete the following tasks
Task 1: Project Overview
Task 2: Introduction to Google Colab and Importing Libraries
Task 3: Importing and Exploring Dataset
Task 4: Image Pre-Processing
Converting image to grayscale
Applying histogram equalization technique
Normalization
Task 5: Build a deep convolutional network model using Keras
Task 6: Compile and train the model
Task 7: Testing model with the test dataset & assess the performance of trained Convolutional Neural Network model
Task 8: Saving the trained model
We’ll be carrying out our entire project in Google Colab environment. That's why pre-installation of libraries and dependencies are not required.
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FILE LIST
Filename
Size
~Get Your Files Here !/1. Introduction/1. Project Overview.mp4
27.2 MB
~Get Your Files Here !/1. Introduction/1. Project Overview.srt
4.8 KB
~Get Your Files Here !/2. Introduction To Project Platform/1. Importing Necessary Libraries in Google Colab Platform.mp4
34.2 MB
~Get Your Files Here !/2. Introduction To Project Platform/1. Importing Necessary Libraries in Google Colab Platform.srt
7.4 KB
~Get Your Files Here !/3. Cloning Traffic Sign Dataset/1. Import, Explore and Visualize Dataset.mp4
77.6 MB
~Get Your Files Here !/3. Cloning Traffic Sign Dataset/1. Import, Explore and Visualize Dataset.srt
8.5 KB
~Get Your Files Here !/4. Image Pre-Processing/1. Grayscale Conversion , Applying Histogram Equalization and Normalization.mp4
55.5 MB
~Get Your Files Here !/4. Image Pre-Processing/1. Grayscale Conversion , Applying Histogram Equalization and Normalization.srt
7 KB
~Get Your Files Here !/5. Build, Compile and Train a Deep Learning Model/1. Overview of Neural Networks.mp4
120.8 MB
~Get Your Files Here !/5. Build, Compile and Train a Deep Learning Model/1. Overview of Neural Networks.srt
18.3 KB
~Get Your Files Here !/5. Build, Compile and Train a Deep Learning Model/1.1 httpswww.cs.ryerson.ca~aharleyvisconvflat.html.html
114 B
~Get Your Files Here !/5. Build, Compile and Train a Deep Learning Model/2. Train a Deep Learning Model that can identify between 43 different Traffic Signs.mp4
88.2 MB
~Get Your Files Here !/5. Build, Compile and Train a Deep Learning Model/2. Train a Deep Learning Model that can identify between 43 different Traffic Signs.srt
11.5 KB
~Get Your Files Here !/6. Testing and Analyzing The Performance of the Model/1. Overfitting.mp4
6.9 MB
~Get Your Files Here !/6. Testing and Analyzing The Performance of the Model/1. Overfitting.srt
2.9 KB
~Get Your Files Here !/6. Testing and Analyzing The Performance of the Model/2. Testing and Saving the Model.mp4
74.7 MB
~Get Your Files Here !/6. Testing and Analyzing The Performance of the Model/2. Testing and Saving the Model.srt
11.6 KB
~Get Your Files Here !/6. Testing and Analyzing The Performance of the Model/2.1 Downloadable Colab Notebook link.html
