Deep Learning – Neural Networks And Heuristics With R

Free Download Deep Learning – Neural Networks And Heuristics With R
Published 1/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.08 GB | Duration: 6h 10m
Confidently build predictive Machine Learning and Deep Learning models using R to solve business problems

What you'll learn
Learn how to solve real life problem using the deep learning techniques
Learn Deep Learning models such as Regression, Heauristic etc
Understanding of basics of statistics and concepts of Deep Learning
How to do basic statistical operations and run ML models in R
Requirements
People Wanting To Master The R & R Studio Environment For Data Science
Anyone With Prior Exposure To Common Machine Learning Concepts Such As Supervised Learning
Description
This course covers the main aspects of neural networks and deep learning. If you take this course, you can do away with taking other courses or buying books on R based data science. In this age of big data, companies across the globe use R to sift through the avalanche of information at their disposal. By becoming proficient in neural networks and deep learning in R, you can give your company a competitive edge and boost your career to the next level.You're looking for a complete Machine Learning and Deep Learning course that can help you launch a flourishing career in the field of Deep Learning, R, right? You've found the right Deep Learning course! After completing this course you will be able to:Confidently build predictive Machine Learning and Deep Learning models using R to solve business problems and create business strategyAnswer Machine Learning, Deep Learning, R, related interview questionsParticipate and perform in online Data Analytics and Data Science competitions such as Kaggle competitionsLearn how to solve real life problem using the deep learning techniquesdeep Learning models such as Regression, Heauristic etcUnderstanding of basics of statistics and concepts of Deep LearningHow to do basic statistical operations and run ML models in RIn-depth knowledge of data collection and data preprocessing for Machine Learning problemHow to convert business problem into a Machine learning problem
Overview
Section 1: Deep Learning: Neural Networks With R
Lecture 1 Reviewing Dataset
Lecture 2 Creating Dataframes
Lecture 3 Generating Output
Lecture 4 Running Neural Network Code
Lecture 5 Importing Dataset
Lecture 6 Neural Network Plots for Hidden Layer 1
Lecture 7 Syntax and Commands for MLP
Lecture 8 Running the Code
Lecture 9 Testing for Dataframes
Lecture 10 Predict Results
Lecture 11 Creating R Folder
Lecture 12 Generating Output Plot
Lecture 13 Testing and Predicting the Outputs
Section 2: Deep Learning: Heuristics Using R
Lecture 14 Course Contents
Lecture 15 Creating Dataframes
Lecture 16 Generating Descriptive
Lecture 17 Generating Descriptive Continued
Lecture 18 Setting Directory and Environment
Lecture 19 Assigning Variables
Lecture 20 Syntax and Command Part 1
Lecture 21 Syntax and Command Part 2
Lecture 22 Syntax and Command Part 3
Lecture 23 Setting Directory and Environment-Cryptocurrencies
Lecture 24 Spearman Techniques
Lecture 25 Generating Line Graphs
Lecture 26 Generating Scatter Plots
Lecture 27 Generating Multiple Scatter Plots
Lecture 28 Understanding Regression Modeling Theory
Lecture 29 Implementing Linear Regression Modeling
Lecture 30 Syntax and Commands
Lecture 31 Generating Scatter Plots-Energy Sector
Lecture 32 Multiple Scatter Plots
Lecture 33 Creating Dataframes-Financial Markets
Lecture 34 Understanding Multiple
Lecture 35 Implementing Multiple Regression Model in R
Lecture 36 Plot and Draw Line of Fit
Lecture 37 Multiple Scatter Plots in a Graphical Frame
People pursuing a career in data science,Working Professionals beginning their Data journey,Statisticians needing more practical experience

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