The cryptocurrency industry has a reputation for being volatile, unpredictable, and ever-changing. Predicting the way that the market would move could easily give an advantage to the everyday investor, and one data scientist believes that he's figured it out. Abinhav Sagar of the prestigious Vellore Institute of Technology recently stated that it is possible to use a Long Short-Term Memory (LSTM) neural network to predict these prices with real-world accuracy. Sagar published a blog about this exact method on December 2nd, showing the four steps he can take with the technology to create predictions in a "relatively unpredictable" market. The demonstration started with a comment from Sagar that the application of this machine learning tech has been relatively limited in the cryptocurrency sector, even though it has had some success in the stock market.

Data scientists and machine learning engineers in India make about one-tenth of what their counterparts in the United States do, a leading global survey shows. The median annual salary in India, based on 450 responses, is $11,715 (Rs 7.5 lakhs), a fraction of the comparable annual earnings in the US ($110,000). The median for all respondents from 52 countries, whose data was considered in the calculations, is $55,441. Kaggle, the world's largest global online community of data scientists, statisticians and machine learning engineers, published its The State of Data Science & Machine Learning annual survey earlier this week, deriving insights on 16,000 respondents in a report that polled the data science and machine learning industry. The Google-owned platform currently boasts of over a million members and is known to attract the world's smartest data scientists by holding public and private data science competitions.