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MACHINE LEARNING FOR BEGINNERS

Posted By: TiranaDok
MACHINE LEARNING FOR BEGINNERS

MACHINE LEARNING FOR BEGINNERS: A Complete Step-By-Step Practical User Guide For An Absolute Beginner To Master And Understand ML (Python, Numpy, Pandas, KNN, Bias And Variance, Deep Learning Manual) by THOMAS SANCHEZ
English | 2022 | ISBN: N/A | ASIN: B0B929RSD8 | 230 pages | MOBI | 4.92 Mb

Machine Learning is gradually changing the world!

With the widespread availability of computers today, most machine learning techniques can be done at home.
Machine learning is a way to automate and improve how computers learn from their experiences without being programmed, i.e. without any help from a person. We train our machines (computers) by using the data and different algorithms to build machine learning models. It is a subfield of artificial intelligence (AI) that allows computers to "learn" without being explicitly programmed from training data and improve over time. Machine learning is becoming more relevant to our lives every day.
Machine Learning for Beginners has been written and designed for a complete beginner to master and understand machine learning. This easy-to-follow guide contains practical examples & illustrations for learning machine learning

This Is The Preview Of The Guide:
  • Basics Of Machine Learning
  • What Exactly Is Machine Learning
  • Terminologies Of Machine Learning
  • How Does Machine Learning Work
  • How To Become A Machine Learning Engineer
  • Python Libraries For Machine Learning
  • Understanding NumPy
  • Understanding Pandas
  • What Are Pandas In Python?
  • Toolbar For Machine Learning
  • Setting Up Your Data
  • Linear Regression
  • Understanding And Using The Knn Algorithm
  • How Does KNN Work?
  • Everything You Need To Know About Bias And Variance
  • Errors In Machine Learning
  • What Exactly Is Bias?
  • Understanding Artificial Neural Network
  • Understanding Decision Tree
  • Important Terms In Decision Trees
  • Assumption In Decision Tree
  • Ensembling Model In Machine Learning
  • How To Use Bayesian Optimization
  • Why Should You Learn Machine Learning
  • Career In Machine Learning
  • And A Lot More!