Machine Learning: Learn By Building Web Apps in Python

[Panter]

Machine Learning: Learn By Building Web Apps in Python
Published 09/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 91 lectures (18h 1m) | Size: 7.2 GB

Learn basic to advanced Machine Learning algorithms by creating web applications using Flask!!



What you'll learn
Master Machine Learning on Python
Learn about Regression, Classification tasks
Learn about neural networks
Learn about Deep neural networks with projects
Create web applications using flask
Simple Model building with Scikit-Learn , TensorFlow and Keras
Creating REST API for Machine Learning models
Learn about Exploratory Data Analysis
Implement linear, logistic regression
Implement convolution neural network
Learn about Postman to test API endpoints


Requirements
Any laptop and an internet connection
Basic knowledge of Python programming is must


Description
Machine learning is a branch of artificial intelligence (AI) focused on building applications that learn from data and improve their accuracy over time without being programmed to do so.

In data science, an algorithm is a sequence of statistical processing steps. In machine learning, algorithms are 'trained' to find patterns and features in massive amounts of data in order to make decisions and predictions based on new data. The better the algorithm, the more accurate the decisions and predictions will become as it processes more data.

Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts.

Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning.

Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.

Topics covered in this course

1. Warm-up with Machine learning Libraries: numpy, pandas

2. Implement Machine Learning algorithms: Linear, Logistic Regression

3. Implement Neural Network from scratch

4. Introduction to Tensorflow and Keras

5. Start with simple "Hello World" flask application

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

7. Implement transfer learning and built an app to implement image classification

Who this course is for
Programmer who wants to learn machine learning by creating web applications
Data Scientists who want to know how to test & monitor their models beyond
Beginner Python programmer
Machine Learning engineer who wants to create fun projects using their basic skills

Homepage

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