Curriculum
- 3 Sections
- 30 Lessons
- Lifetime
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- Overview of Project9
- 1.1Introduction [Video]10 Minutes
- 1.2Project Scope and Objectives8 Minutes
- 1.3How to Go About3 Minutes
- 1.4Study Along2 Minutes
- 1.5Use of ChatGPT2 Minutes
- 1.6Project Code2 Minutes
- 1.7Setting up your Project Development Environment3 Minutes
- 1.8Setting up your Local (Laptop/Desktop) Environment6 Minutes
- 1.9Project Steps8 Minutes
- Exploratory Data Analysis (EDA) Phase6
- Machine Learning Model Building15
- 3.2Understanding CNNs [Video]10 Minutes
- 3.3Convolutions and Pooling Concepts of CNN15 Minutes
- 3.4Why CNNs for the CIFAR-10 Problem6 Minutes
- 3.5CNN Architecture for this Project10 Minutes
- 3.6What do the Convolutional Layers learn and what do Pooling Layers learn?10 Minutes
- 3.7What is the Calculation of Convolution Layers Input to output?10 Minutes
- 3.8What are the Calculation of the Pooling Layers Input to Output?10 Minutes
- 3.9What is ReLU and what is it doing here on the Conv Layers in this Project?
- 3.10How does the model optimisation happen through the CNN learning Epochs12 Minutes
- 3.11Classification Error and Metrics [Video]10 Minutes
- 3.12Model Coding [Video]8 Minutes
- 3.13What is the Model Pickle5 Minutes
- 3.14Streamlit Deployment [Video]10 Minutes
- 3.15Streamlit Features7 Minutes
- 3.16Code ZIP10 Minutes
Streamlit Features
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