Julia vs. Python: Which is best for data science

Among the many use cases Python covers, data analytics has become perhaps the biggest and most significant. The Python ecosystem is loaded with libraries, tools, and applications that make the work of scientific computing and data analysis fast and convenient. But for the developers behind the Julia language — aimed specifically at “scientific computing, machine learning,… Continue reading Julia vs. Python: Which is best for data science

TensorFlow 2 review: Easier, end-to-end machine learning

The importance of machine learning and deep learning is no longer in doubt. After decades of promise, hype, and disappointment, both have led to practical applications. We haven’t gotten to the point where machine learning or deep learning applications are perfect, but many are very good indeed. To read this article in full, please click… Continue reading TensorFlow 2 review: Easier, end-to-end machine learning

Supervised learning explained

Machine learning is a branch of artificial intelligence that includes algorithms for automatically creating models from data. At a high level, there are four kinds of machine learning: supervised learning, unsupervised learning, reinforcement learning, and active machine learning. Since reinforcement learning and active machine learning are relatively new, they are sometimes omitted from lists of… Continue reading Supervised learning explained