Machine Learning Regression Masterclass in Python
Link : Machine Learning Regression Masterclass in Python
Udemy course
Build 8+ Practical Projects and Master Machine Learning Regression Techniques Using Python, Scikit Learn and Keras
What you'll learn
Artificial Intelligence (AI) revolution is here! The technology is progressing at a massive scale and is being widely adopted in the Healthcare, defense, banking, gaming, transportation and robotics industries.
Machine Learning is a subfield of Artificial Intelligence that enables machines to improve at a given task with experience. Machine Learning is an extremely hot topic; the demand for experienced machine learning engineers and data scientists has been steadily growing in the past 5 years. According to a report released by Research and Markets, the global AI and machine learning technology sectors are expected to grow from $1.4B to $8.8B by 2022 and it is predicted that AI tech sector will create around 2.3 million jobs by 2020.
Link : Optimization with Metaheuristics in Python
Udemy course
Learn Simulated Annealing, Genetic Algorithm, Tabu Search, and Evolutionary Strategies, and Learn to Handle Constraints
Bestseller
Link : Machine Learning Optimization Using Genetic Algorithm
Udemy course
Learn how to optimize Machine Learning algorithms' performances and apply feature selection using Genetic Algorithm
What you'll learn
In this course, you will learn what hyperparameters are, what Genetic Algorithm is, and what hyperparameter optimization is. In this course, you will apply Genetic Algorithm to optimize the performance of Support Vector Machines (SVMs) and Multilayer Perceptron Neural Networks (MLP NNs). It is referred to as hyperparameter tuning or parameter tuning. You will also learn how to do feature selection using Genetic Algorithm.
Udemy course
Build 8+ Practical Projects and Master Machine Learning Regression Techniques Using Python, Scikit Learn and Keras
What you'll learn
- Master Python programming and Scikit learn as applied to machine learning regression
- Understand the underlying theory behind simple and multiple linear regression techniques
- Apply simple linear regression techniques to predict product sales volume and vehicle fuel economy
- Apply multiple linear regression to predict stock prices and Universities acceptance rate
- Cover the basics and underlying theory of polynomial regression
- Apply polynomial regression to predict employees’ salary and commodity prices
Artificial Intelligence (AI) revolution is here! The technology is progressing at a massive scale and is being widely adopted in the Healthcare, defense, banking, gaming, transportation and robotics industries.
Machine Learning is a subfield of Artificial Intelligence that enables machines to improve at a given task with experience. Machine Learning is an extremely hot topic; the demand for experienced machine learning engineers and data scientists has been steadily growing in the past 5 years. According to a report released by Research and Markets, the global AI and machine learning technology sectors are expected to grow from $1.4B to $8.8B by 2022 and it is predicted that AI tech sector will create around 2.3 million jobs by 2020.
Link : Optimization with Metaheuristics in Python
Udemy course
Learn Simulated Annealing, Genetic Algorithm, Tabu Search, and Evolutionary Strategies, and Learn to Handle Constraints
Bestseller
Link : Machine Learning Optimization Using Genetic Algorithm
Udemy course
Learn how to optimize Machine Learning algorithms' performances and apply feature selection using Genetic Algorithm
What you'll learn
- Apply Genetic Algorithm to optimize Machine Learning algorithms
- Apply Genetic Algorithm on Support Vector Machines and Multilayer Perceptron Neural Networks
- Apply Genetic Algorithm for Feature Selection
- Learn how to code Genetic Algorithm in Python from scratch
In this course, you will learn what hyperparameters are, what Genetic Algorithm is, and what hyperparameter optimization is. In this course, you will apply Genetic Algorithm to optimize the performance of Support Vector Machines (SVMs) and Multilayer Perceptron Neural Networks (MLP NNs). It is referred to as hyperparameter tuning or parameter tuning. You will also learn how to do feature selection using Genetic Algorithm.
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