Goto

Collaborating Authors

Results


Machine Learning in R & Predictive Models

#artificialintelligence

My course will be your complete guide to the theory and applications of supervised & unsupervised machine learning and predictive modeling using the R-programming language. Unlike other courses, it offers NOT ONLY the guided demonstrations of the R-scripts but also covers theoretical background that will allow you to FULLY UNDERSTAND & APPLY MACHINE LEARNING & PREDICTIVE MODELS (K-means, Random Forest, SVM, logistic regression, etc) in R (many R packages incl. This course also covers all the main aspects of practical and highly applied data science related to Machine Learning (classification & regressions) and unsupervised clustering techniques. Thus, if you take this course, you will save lots of time & money on other expensive materials in the R based Data Science and Machine Learning domain. In this age of big data, companies across the globe use R to analyze big volumes of data for business and research.


Machine Learning Towards Intelligent Systems: Applications, Challenges, and Opportunities

arXiv.org Artificial Intelligence

The emergence and continued reliance on the Internet and related technologies has resulted in the generation of large amounts of data that can be made available for analyses. However, humans do not possess the cognitive capabilities to understand such large amounts of data. Machine learning (ML) provides a mechanism for humans to process large amounts of data, gain insights about the behavior of the data, and make more informed decision based on the resulting analysis. ML has applications in various fields. This review focuses on some of the fields and applications such as education, healthcare, network security, banking and finance, and social media. Within these fields, there are multiple unique challenges that exist. However, ML can provide solutions to these challenges, as well as create further research opportunities. Accordingly, this work surveys some of the challenges facing the aforementioned fields and presents some of the previous literature works that tackled them. Moreover, it suggests several research opportunities that benefit from the use of ML to address these challenges.


All-in-One:Machine Learning,DL,NLP,AWS Deply [Hindi][Python]

#artificialintelligence

Online Courses Udemy - All-in-One:Machine Learning,DL,NLP,AWS Deply [Hindi][Python], Complete hands-on Machine Learning Course with Data Science, NLP, Deep Learning and Artificial Intelligence Created by Rishi Bansal English Students also bought Java from Zero to First Job: Part 1 - Java Basics and OOP C Programming for Beginners - Master the C Fundamentals Full-Stack Web Development For Beginners The Complete Java Programmer: From Scratch to Advanced Python and Django Full-Stack Web Development for beginners Learn To Create AI Assistant (JARVIS) With Python Preview this course GET COUPON CODE Description This course is designed to cover maximum Concept of Machine Learning. Anyone can opt for this course. No prior understanding of Machine Learning is required. As a Bonus Introduction Natural Language Processing and Deep Learning is included. Below Topics are covered Chapter - Introduction to Machine Learning - Machine Learning?


Top 5 Essential Machine Learning Algorithms Data Scientists Should Learn

#artificialintelligence

Hello guys, you may know that Machine Learning and Artificial Intelligence have become more and more important in this increasingly digital world. They are now providing a competitive edge to businesses like NetFlix's Movie recommendations. If you have just started in this field and looking for what to learn then I am going to share 5 essential Machine learning algorithms you can learn as a beginner. These essential algorithms form the basis of most common Machine learning projects and having a good knowledge of them will not only help you to understand the project and model quickly but also to change them as per your need. Machine learning by a simple word is the science or the field of making the computer learn like a human by feeding it with the data and without being programmed and it separate into two categories the first one is classification problems which the machine needs to classify between two objects or more like between human and animal and the second is regression problems which the machine need to produce an output based on a previous data.


Introduction to Machine Learning in R

#artificialintelligence

This course material is aimed at people who are already familiar with ... What you'll learn This course is about the fundamental concepts of machine learning, facusing on neural networks. This topic is getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detect cancer for example. We may construct algorithms that can have a very good guess about stock prices movement in the market.


Fundamentals of Machine Learning [Hindi][Python]

#artificialintelligence

Online Courses Udemy - Machine Learning, Fundamentals of Machine Learning [Hindi][Python] Complete hands-on Machine Learning Course with Data Science, NLP, Deep Learning and Artificial Intelligence Created by Rishi Bansal English Students also bought Machine Learning and AI: Support Vector Machines in Python Data Science: Supervised Machine Learning in Python Machine Learning A-Z: Hands-On Python & R In Data Science Machine Learning, Data Science and Deep Learning with Python Data Science and Machine Learning Bootcamp with R Machine Learning Practical: 6 Real-World Applications Preview this course GET COUPON CODE Description This course is designed to understand basic Concept of Machine Learning. Anyone can opt for this course. No prior understanding of Machine Learning is required. NOTE: Course is still under Development. You will see new topics will get added regularly. Now question is why this course?


Data Science & Machine Learning For Non Technical Executives

#artificialintelligence

Udemy Course Data Science & Machine Learning For Non Technical Executives NED Data Science & Machine Learning For Non Technical Executives free download also includes 8 hours on-demand video, 3 articles, 34 downloadable resources, Full lifetime access by Ankit Mistry Basic idea bout Machine learning technology Different ML algorithm like Regression, Classification & Clustering KNN and Logistic Regression algorithm Linear and Multiple Regression K means Clustering algorithm Overview about Deep Learning, Computer Vision Field Description Welcome to course on Data Science & Machine Learning For Non Technical Executives. Disclaimer: This is not python based machine learning course. I would highly suggest you not to enroll in this course if you are interested in implementation part of machine learning algorithm. There are many course on Udemy which teach machine learning with R/Python. I have designed this course for absolute beginner and non technical people who just want to start diving into machine learning world.


What is Machine Learning? Types of Machine Learning Algorithms

#artificialintelligence

Machine learning is the concept of using the different sample data model to create a mathematical model to understand the specific task. As machine learning deals with business problems the other name for machine learning is predictive analysis. The Supervised machine learning algorithm, unsupervised algorithm, Semi-supervised algorithm, and reinforcement machine learning algorithm are the algorithms of machine learning which are used to make the computers to learn by experience. There are UG courses, PG courses and online courses for cloud computing. Some of the courses are offered with no eligibility criteria whereas some degree programs with cloud computing demand for entrance exams like JEE Main, JEE Advanced, VITEEE, IPU CET, SRMJEEE, and MHT CET. Machine learning and Artificial Intelligence are two different concepts used for training machines and learning data from machines with algorithms. Machine learning is one of the applications and a subset of artificial intelligence. An automated learning system with the experience or patterns of examples initiates the process of automated predictions.



24 Best Data Science Certification & Courses 2019 Digital Learning Land

#artificialintelligence

Are you looking for Best Data Science Certification? With these best data science online courses, Degree, Training, Classes, and Tutorial 2019 you can improve your precise skills and become a Data Scientist. Data science introduces the incorporation of programming, statistical skills, machine learning, and algorithms. These best Data Science tutorials will make you skilled in all insights of Data Science. In this modernized time, most organizations and companies are opening their opportunity to Data Science. Companies are now concentrating on Data Science to increase their business. So there is a huge demand for data scientist and people who are interested to build their career in this field there is a tremendous chance for them. Data Science is a method that combines numerous segments. In these following courses, you will gain in-depth knowledge of Data Science. Python is one of the high-level programming languages. Those who are highly interested in machine learning this course is suggested to them. This course is an overview of machine learning both in python and R. This course is the BESTSELLER course of Machine Learning. Anyone who is not satisfied with his job to want to become a data scientist and want to start a career in data science highly recommended to do this course. This course will explore all the different fields of machine learning. The purpose of courses to teach the learner how to create machine learning algorithms in Python and R from to data science experts. This is the BESTSELLER course. If you want to learn how you will be the master in machine learning on Python and R this course is for you. Super Data science team and super data science support also instructed this course. This instructors doing their job creatively for covering all the gaps of the learner also provides helps for the better of the learning process. About 380,693 students enrolled in this course and the rating is 4.5.