Hill Climbing Algorithm | Hill Climbing in Artificial Intelligence | Data Science Tutorial | Edureka

* Machine Learning Engineer Masters Program: *
Hill Climbing is an Algorithm is one that will find you the best possible solution to your problem in the most reasonable period of time! This tutorial is a complete breakdown of the algorithm also implemented in Python using a Jupyter Notebook. Following are the topics ;

01:38 What is HIll Climbing?
06:47Types of Hill Climbing
10:35 Example of HIll Climbing in Python
14:56 Complexities
16:26 Applications

Jupyter notebook tutorial:

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About the Masters Program

Edureka’s Machine Learning Engineer Masters Program makes you proficient in techniques like Supervised Learning, Unsupervised Learning and Natural Language Processing. It includes training on the latest advancements and technical approaches in Artificial Intelligence & Machine Learning such as Deep Learning, Graphical Models and Reinforcement Learning.


The Master's Program Covers Topics LIke:
Python Programming
PySpark
HDFS
Spark SQL
Machine Learning Techniques and Artificial Intelligence Types
Tokenization
Named Entity Recognition
Lemmatization
Supervised Algorithms
Unsupervised Algorithms
Tensor Flow
Deep learning
Keras
Neural Networks
Bayesian and Markov’s Models
Inference
Decision Making
Bandit Algorithms
Bellman Equation
Policy Gradient Methods.

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Prerequisites

There are no prerequisites for enrolment to the Masters Program. However, as a goodwill gesture, Edureka offers a complimentary self-paced course in your LMS on SQL Essentials to brush up on your SQL Skills. This program is designed and developed for aspirant planning to build a career in Machine Learning or an experienced professional working in the IT industry.

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