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A tutorial To Find Best Scikit classifiers For Sentiment Analysis

@machinelearnbot

So, Naive Bayes gives very bad result. It can just predict 11% of bad comments. SGDClassifier predicted 47% of bad comments correctly which is a considerable improvement over the Naive Bayes. Logistic Regression though has regression in its surname but its a classifier and it shows good improvement over SGDClassifier. SVC comes out as winner with 66 % correct prediction for sentiment analysis.


Species Distribution Models with GIS & Machine Learning in R

@machinelearnbot

Are You an Ecologist or Conservationist Interested in Learning GIS and Machine Learning in R? Then this course is for you! I will take you on an adventure into the amazing of field Machine Learning and GIS for ecological modelling. You will learn how to implement species distribution modelling/map suitable habitats for species in R. My name is MINERVA SINGH and i am an Oxford University MPhil (Geography and Environment) graduate. I finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life spatial data from different sources and producing publications for international peer reviewed journals.


How to Install XGBoost for Python on macOS - Machine Learning Mastery

#artificialintelligence

XGBoost is a library for developing very fast and accurate gradient boosting models. It is a library at the center of many winning solutions in Kaggle data science competitions. In this tutorial, you will discover how to install the XGBoost library for Python on macOS. How to Install XGBoost for Python on macOS Photo by auntjojo, some rights reserved. Note: I have used this procedure for years on a range of different macOS versions and it has not changed.


โ€“ Tutorial on robotics for developers - Nicolรฒ Valigi

@machinelearnbot

I've written a project-based tutorial to introduce other developers to the exciting world of robotics software. By the end of it, you'll have created a fairly complete SLAM system that uses cameras and IMUs for localizing a robot. The project is built using some of the most common technologies, including ROS and OpenCV and requires some proficiency in C programming and Linux. I've assumed no previous knowledge in computer vision or robotics, though. If you want to have a look before starting to read, the source code is available on GitHub.


Deep Learning and NLP A-Z : How to create a ChatBot

@machinelearnbot

We've talked about, speculated and often seen different applications for Artificial Intelligence - But what about one piece of technology that will not only gather relevant information, better customer service and could even differentiate your business from the crowd? ChatBots are here, and they came change and shape-shift how we've been conducting online business. Fortunately technology has advanced enough to make this a valuable tool something accessible that almost anybody can learn how to implement. If you want to learn one of the most attractive, customizable and cutting edge pieces of technology available, then this course is just for you!


Learn Robotics - Become a Robotics Engineer Udacity

#artificialintelligence

The field of robotics is growing at an incredible rate, and demand for software engineers with the right skills far exceeds the current supply. This makes this an ideal time to enter this field, and this groundbreaking program represents a unique opportunity to develop these in-demand skills. Expert instructors, personalized project reviews, and exclusive hiring opportunities are hallmarks of this program, and in collaboration with the NVIDIA Deep Learning Institute--one of the most exciting and innovative companies in the world--we have built an unrivalled curriculum that offers the most cutting-edge learning experience currently available. You will graduate from this program having completed several hands-on robotics projects in simulation that will serve as portfolio pieces demonstrating the skills you've acquired. This will enable you to pursue a rewarding career in the robotics field.


13 Best Free Online Resources/Books to learn R and Data Science

@machinelearnbot

It is online only book developed by Chester Ismay and Albert Y. Kim and covers the basics of using R to analyze data and create data stories using R and statistics. Check the samples of "data stories" from one of the classes here from one of the authors of the book.


How (and Where) to Get a Great Crash Course in AI NVIDIA Blog

#artificialintelligence

Artificial intelligence is years, even decades, from replicating functions of the human mind, but it's still getting serious work done today. And its influence will only expand. The irony of all that promise: Human minds are way behind. Relatively few have a baseline understanding about how AI and deep learning truly work. Techniques like machine learning, which underpin many of today's AI tools, aren't easy to grasp.


Delhi: Starting July, college course on artificial intelligence

#artificialintelligence

The Indraprastha Institute of Information Technology-Delhi (IIIT-D) is set to start a new M.Tech programme in artificial intelligence at the Infosys Centre for Artificial Intelligence, starting July 2018. The Institute will advertise for the programme in March-April. The programme, touted to be the first of its kind in the city, will prepare students to work in the industry as well as pursue further research in the subject. The fee structure will be the same as for other courses. The Infosys Centre for Artificial Intelligence was set up in 2016 in partnership with Infosys, which gave a grant of Rs 24 crore.


Learning Path: Data Science With Apache Spark 2

@machinelearnbot

The real power and value proposition of Apache Spark is its speed and platform to execute data processing and data science tasks. Let's see how easy it is! Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. Spark is one of the most widely-used large-scale data processing engines and runs extremely fast. It is a framework that has tools that are equally useful for application developers as well as data scientists.