Cryptocurrencies apparently gained skyrocketing popularity in 2017 because of the exponential growth of crypto coin’s market cap for numerous consecutive months. In January 2018, the prices went above eight hundred billion dollars. Now when it comes to the price predictions, machine learning proved to be fairly successful in anticipating the prices in stock market. It makes use of a myriad of diverse models based on time series and historical data.

The application of the models that are utilized in the stock market is quite restrictive for the crypto prices predictions. The biggest reason behind it is that the cryptocurrencies’ prices depend upon multiple factors, including political factors, security issues, economic problems, pressure on global markets for maximum delivery, internal competition, and above all technological progress. The high volatility of crypto coins offer huge potential to make great profits if smart investment strategies are employed.

It is unfortunate that there is a serious dearth of indexes related to cryptocurrencies. That is what makes crypto market much more unpredictable as compared to the conventional fiscal predictions, such as the ones that are taken place in the stock markets.

What Deep Learning Really Is?

Deep learning’s basically machine learning’s subset, and the primary difference between both of them is very interesting. Deep learning makes use of the neural networks that enables machines to train their own selves. Machine learning needs algorithms along with the parameters that are determined by either engineer or user for the training of machine.

It would be safe to say that machine learning demands more care and hands-on fixing and tweaking as compared to the deep learning. On the contrary, deep learning has the competence to conduct all the fixing and tweaking without having the need of any engineer’s/user’s practical interference. The notable thing is that deep learning requires creating or tweaking neural networks themselves, which present their own unique obstacles.

Will Deep Learning Be More Effective Than Machine Learning to Predict Cryptocurrency Prices?

If you are planning to invest in crypto currency, you will naturally be curious about the technologies and models that are being employed for the prediction of crypto prices. A question might also pop up into your mind that will the employment of deep learning in place of machine learning be more effective and beneficial for the anticipation of crypto coin’s prices?

The answer to this question essentially depends upon the problem at hand. In several cases, conventional models of machine learning perform much better as compared to intricate neural networks. Fitting and training of the tabular data in order to conduct classification is one of those instances. Under such scenarios, the time that neural networks take to train is considerably longer. However, neural networks perform either at an equal or lesser level relative to the conventional classification algorithms.

Things become a little different when it comes to the cryptocurrencies’ time-series and historical data analysis. Deep learning can be significantly helpful in processing the historical data of crypto currencies which will eventually assist in making fairly accurate predictions regarding their future prices.

What Does the Procedure of Crypto Prices Predictions Via Deep Learning Include?

Different steps are involved in the development of a deep learning model from scratch for the sake of conducting crypto prices predictions. Some of the major steps of this procedure may include:

• Obtaining real time data of cryptocurrency.
• Preparing data in order to do testing and training.
• Predicting cryptocurrency prices with the help of a neural network like LSTM.
• Visualizing the results of prediction.

With the help of deep learning model, the goal is to forecast prices of cryptocurrency by making the most out of all available features of trading, including volume, prices, low, high open values that are available in the crypto dataset. It is possible to download dataset from various websites, such as CryptoCompare.

 Once data is gathered, the process of coding can be started by loading all the required dependencies and libraries. In addition to it, you will also have to develop and execute a neural network like LSTM. It is very important to implement LSTM in order to conduct cryptocurrency prices predictions particularly with the help of deep learning so that you can invest in crypto currency more confidently.