Brief Introduction
Machine Learning using R Programming and Python ProgrammingDescription
This course has been prepared for professionals aspiring to learn the basics of R and Python and develop applications involving machine learning techniques such as recommendation, classification, regression and clustering.
Through this course, you will learn to solve data-driven problems and implement your solutions using the powerful yet simple programming language like R and Python and its packages.
After completing this course, you will gain a broad picture of the machine learning environment and the best practices for machine learning techniques.
Requirements
- Requirements
- Before you start proceeding with this course, we assume that you have a prior exposure to R packages and Python, Numpy, pandas, scipy, matplotlib, Windows and any of the Linux operating system flavors. If you are new to any of these concepts, here you can learn all the concepts from basics on wards.
DATAhill Solutions Srinivas Reddy
3.7 Raiting
Data Science: Supervised Machine Learning in Python
- 4.8
-
![]()
![]()
![]()
![]()
![]()
Full Guide to Implementing Classic Machine Learning Algorithms in Python and with Scikit-Learn In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning....
The Complete Guide to TensorFlow 1.x
- 4
-
![]()
![]()
![]()
![]()
![]()
Become an expert in machine learning and deep learning with the new TensorFlow 1. x If yes, then this course is for you!...
Real-World Data Science with Spark 2
- 4
-
![]()
![]()
![]()
![]()
![]()
Address Big Data challenges with the fast and scalable features of Spark. Are you looking forward to expand your knowledge of performing data science operations in Spark?...
Analyze Datasets and Train ML Models using AutoML
- 4.6
-
![]()
![]()
![]()
![]()
![]()
In the first course of the Practical Data Science Specialization, you will learn foundational concepts for exploratory data analysis (EDA), automated machine learning (AutoML), and text classification algorithms....
