Download Machine Learning: Learn By Building Web Apps in Python

What you would learn in Machine Learning: Learn By Building Web Apps in Python course?

Machine learning can be described as Artificial Intelligence (AI) that focuses on creating applications that can learn from data and increase their performance over time without being programmed.

In data science, algorithms are a series of steps in statistical processing. Machine learning algorithms are trained to identify patterns and characteristics in large quantities of data to make predictions and decisions based on the latest data. The more efficient the algorithm, the more accurate its predictions and decisions will be when processing more information.

Machine learning has brought astonishing results, for instance, analyzing medical images and identifying ailments on the same level as human experts.

Google's AlphaGo program beat an international champion in the strategy game by using deep reinforcement learning.

Machine learning is being utilized to create self-driving cars, which will forever transform the auto industry. Imagine a world that has significantly reduced car accidents simply by eliminating human error.

The subjects that are covered in this course include:

1. Warm-up with Machine Learning Libraries: Numpy, Pandas,

2. Implement machine learning algorithms: Logistic, Linear Regression

3. Implement Neural Network from scratch

4. Tensorflow Introduction and Keras

5. Begin with the basic "Hello World" flask application

6. Create an application for the flask to implement linear regression and test API's endpoints

7. Use transfer learning to implement and build an application to implement image classification

Course Content:

• Master Machine Learning on Python
• Learn about the Regression, Classification, and Regression tasks.
• Learn about neural networks
• Find out more about the basics of Deep neural networks through projects
• Create web-based applications with flask
• Simple Model Building using Scikit-Learn, TensorFlow, and Keras
• Creating REST API for Machine Learning models
• Find out more about Exploratory Data Analysis
• Implement logistic regression, linear regression
• Implement a convolution neural network
• Learn more about Postman for testing API endpoints

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