dSPP is the world first interactive database of proteins for AI and Machine Learning, and is fully integrated with Keras and Tensorflow. You can access the database at peptone.io/dspp
Machine Learning applications include evaluation of driver condition or driving scenario classification through data fusion from different external and internal sensors. We examine different algorithms used for self-driving cars.
We show how to use Tableau 10 clustering feature to create statistically-based segments that provide insights about similarities in different groups and performance of the groups when compared to each other.
Nuts-ml is a new data pre-processing library in Python for GPU-based deep learning in vision. It provides common pre-processing functions as independent, reusable units. These so called ‘nuts’ can be freely arranged to build data flows that are efficient, easy to read and modify.
Data Science projects involve iterative processes and may need changes in data at every iteration. But Data versioning, data pipelines and data workflows make Data Scientist’s life easy, let’s see how.
NLG tools automate the analysis and enhance traditional BI platforms by explaining in plain English the significance of visualizations and findings – here is an overview of the market.
Hadoop Distributed File System (HDFS), and Hbase (Hadoop database) are key components of Big Data ecosystem. This blog explains the difference between HDFS and HBase with real-life use cases where they are best fit.
ML modeling is an iterative process and it is extremely important to keep track of all the steps and dependencies between code and data. New open-source tool helps you do that.
The world’s first protein database for Machine Learning and AI
The Machine Learning Algorithms Used in Self-Driving Cars
Text Mining 101: Mining Information From A Resume