Feature hashing is a valuable tool in the data scientist's arsenal. Learn how to use it as a fast, efficient, flexible technique for feature extraction that can scale to sparse, high-dimensional data.
Many articles about machine learning algorithms provide great definitions — but they don't make it easier to choose which algorithm you should use. Enter: this article!
In today's news: Neo4j is announcing Cypher for Apache Spark and the Neo4j Native Graph Platform. Come learn about it all, according to Neo4j's Head of Product Marketing.
Learn about the evolution of neural networks and get a summary of popular Java neural network libraries in this short guide to implementing neural networks from scratch.
Reinforcement learning is a first step towards artificial intelligence that can survive in a variety of environments instead of being tied to certain rules or models.
Big data, IoT, and AI have all contributed to the widespread use of personal info. The privacy debate is at a crossroads where the public, authorities, and companies must decide in which direction the industry will turn.
With the advent of deep learning techniques, MI objectives like automated real-time question-answering, emotional connotation, fighting spam, and more are achieved.
When it comes to caching, what was once a nice-to-have it now a must-have. Check out this detailed article to learn everything you need to know about caching!
TensorFlow and deep learning are things that corporations must now embrace. The coming flood of audio, video, and image data and their applications are key to success.
If you've ever tried to hire anyone, you know how difficult it can be to pour through hundreds of resumes and find the right one. AI can take the pain out of the process!
See how to get started with writing stream processing algorithms using Apache Flink. by reading a stream of Wikipedia edits and getting some meaningful data out of it.
If you've been following software development news recently you probably heard about the new project called Apache Flink. I've already written about it a bit...
We've seen an explosion of interest in machine learning in the past few years. But where did machine learning come from and why is there so much interest in it now?
If you have often wondered to yourself about the difference between machine learning and deep learning, read on to get a detailed comparison in simple layman language.
No more coding for different models, noting down the results, and selecting the best model — AutoML is going to do all of these for you while you brew a cuppa!