Machine Learning training Archives - Page 9 of 9 - DexLab Analytics | Big Data Hadoop SAS R Analytics Predictive Modeling & Excel VBA

If Big Data interests you as a career choice and you are pretty much aware of the skills you need in order to be proficient in this field, in all likelihood you must be aware that R and Python are two leading languages used for analyzing data. And in case you are not really sure as to learn which of the mentioned articles first, this post will help you in making that decision.

In the field of analysis of data, R and Python both are free solutions that are easy to install and get started with. And it is normal for the layman to wonder which to learn first. But you may thank the heavens as both are excellent choices.

Let’s Make Visualizations Better In Python with Matplotlib – @Dexlabanalytics.

A recent poll on the most widely used programming languages for analytics and data science reveal the following:

Reasons to Choose R

R has an illustrious history that stretches for a considerable period of time. In addition you receive support from an active, dedicated and thriving community. That translates to the fact that you are more likely to be helped in case you are in need of some assistance or have any queries to resolve. In addition another factor that works in the favor of R is the abundance of packages that contribute greatly to increasing its functionality and make it more accessible which put R as one of the front runners to being the data science tool of choice. R works well with computer languages like Java, C and C++.

How to Parse Data with Python – @Dexlabanalytics.

In situations that call for heavy tasks in statistical analysis as well as creating graphics R programming is the tool that you want to turn to. In R, you are able to perform convoluted mathematical operations with surprising ease like matrix multiplication. And the array-centered syntax of the language make the process of translating the math into lines of code far easier which especially true of persons with little or no coding knowledge and experience.

Reasons to Opt for Python

In contrast to the specialized nature of R, Python is a programming language that serves general purposes and is able to perform a variety of tasks like munging data, engineering and wrangling data, building web applications and scraping websites amongst others. It is also the easier one to master among the two especially if you have learned an OOP or object-oriented programming language previously. In addition the Code written in Python is scalable and may be maintained with more robust code than it is possible in case of R.

The Choice Between SAS Vs. R Vs. Python: Which to Learn First? – @Dexlabanalytics.

Though the data packages available are not as large and comprehensive as R, Python when used in conjunction with tools like Numpy, Pandas, Scikit etc it comes pretty close to the comprehensive functionality of R. Python is also being adopted for tasks like statistical work of intermediate and basic complexity as well as machine learning.

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According to the experts at Wikipedia Machine Learning happens to be computer science sub-field that has its origins in the detailed examination of recognition of patterns as well as the “computational learning theory” as put into practice in the world of A.I. or artificial intelligence.The subject investigates the study as well as the construction of algorithms which have the ability to pick up skills from and make predictions on the basis of the data that is available.

In this blog post we list some of the key texts that help out students and researchers in this particular field of study.

The Math Behind Machine Learning: How it Works – @Dexlabanalytics.

1. Machine Learning, Neural and Statistical Classification

Edited By: D.J. Spiegelhalter, D. Michie and C.C. Taylor

This book has for its base the ESPRIT or EC project Statlog which compared and made evaluations about a broad range of techniques on classification while at the same time assessing their merits and demerits in addition to applications across the range. The volume listed here is the integrated one which conducts a brief examination of a particular method along with their commercial application to real world scenarios. It encourages cross-disciplinarystudy of the fields of machine learning, neural networks as well as statistics.

Uber: Pioneering Machine Learning into Everything it Does – @Dexlabanalytics.

2. Bayesian Reasoning and Machine Learning

Written By: David Barber

The methods of machine learning have the ability to mine out the values out of data sets that are nothing short of being vast without taxing the computational abilities of the computer. They have established themselves as essential tools in industrial applications of a wide range like analysis of stock markets, search engines as well as sequencing of DNA and locomotion of robots. The field is a promising one and this book helps the students of computer science grasp the tough subject even if their mathematical backgrounds are decent at best.

Pandora: Blending Music with Machine Learning – @Dexlabanalytics.

3. Gaussian Processes for Machine Learning

Authors: Christopher Williams and Carl Rasmussen

Gaussian Processes or more known simply as GPs serve as a practical, principled and probabilistic approach to the learning as conducted in kernel machines. The Machine Learning community has been providing increased attention towards GPs throughout the better part of the last decade and the book serves the important function of sufficing as a unified and systematic treatment of the role of practical as well as theoretical aspect of GPs as present in machine learning. There was a long felt need for such a book and it does not disappoint with its self-contained and comprehensive treatment. This book is highly useful for students as well as researchers in the fields of applied statistics and machine learning.

If your appetite for knowledge on machine learning is far from being satiated, contact DexLab Analytics. It is a pioneering Data Science training institute catering for hundreds of aspiring students. Their analytics courses in Delhi are widely popular.

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Tag: Machine Learning training

Python Vs R- Which You Want To Learn First

Let’s Make Visualizations Better In Python with Matplotlib – @Dexlabanalytics.

A recent poll on the most widely used programming languages for analytics and data science reveal the following:

Reasons to Choose R

How to Parse Data with Python – @Dexlabanalytics.

Reasons to Opt for Python

The Choice Between SAS Vs. R Vs. Python: Which to Learn First? – @Dexlabanalytics.

Interested in a career in Data Analyst?

3 Exceptional Free E-Books On Machine Learning

The Math Behind Machine Learning: How it Works – @Dexlabanalytics.

1. Machine Learning, Neural and Statistical Classification

Uber: Pioneering Machine Learning into Everything it Does – @Dexlabanalytics.

2. Bayesian Reasoning and Machine Learning

Pandora: Blending Music with Machine Learning – @Dexlabanalytics.

3. Gaussian Processes for Machine Learning

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