Data science involves the collecting of data as well as analyzing and interpreting it so that it can be used to make decisions. We are in the internet era where large amounts of data are being collected and stored in cloud sources every day. Data scientists integrate big data and machine learning models to analyze this data.
The entire process of data analysis is a complex one, and thus it needs a machine with a very high computation power. For portability purposes, a laptop with more sophisticated specifications is the best option. But how do you know whether a particular laptop is the right one?
In this article, we will give you a detailed guide that will help you make the correct choice when choosing a laptop for your data science projects. Consider the factors below:
You can find a PC that can execute your data science computations effectively, but it is only best suited at a fixed work station. If your work involves moving from one station to another, then a laptop is the best option. A data scientist needs a machine that is lighter and also has longer battery life. If you need a data scientist, then you can hire one at the Active Wizards website.
As earlier stated, data science tasks require machines with high computation power. If the processing power of that particular machine is low, the computation power will be too. However, a higher processing power tends to affect the portability of the laptop. Laptops with high processing power are often heavier.
At the same time, a laptop with a very high processing power requires more power. This means that the battery life will also be reduced, again affecting portability. Thanks to technology, the introduction of cloud computing is finally helping to strike a balance between portability and processing power. As long as the machine has access to the cloud, then the processing power and portability will not be an issue.
Having said all that, below are the minimum requirements that a laptop should have for it to effectively execute data science tasks.
Random Access Memory (RAM)
A laptop for data science should have at least 8GB of RAM, but one with 16GB of RAM is even better. Data science integrates neural networks and other complex machine learning, all of which require a higher computation speed. 8GB of RAM can do well too, but sometimes you might be required to put your laptop in sleep mode while it is performing computations.
Perhaps this should be first on the list. A machine for data science should run on an NVIDIA GPU. This is because most of the deep learning libraries run on the CUDA processor, which is only compatible with the NVIDIA GPUs. Other than that, you will end up creating low-level codes. An NVIDIA GPU from the 960 series and above should do perfectly.
After the RAM and GPU, the next thing you should check is the processor. An Intel Core i5 of the 7th generation should do fine, but the recommended one is the Intel Core i7 of the seventh generation.
Finally, storage is the other important requirement that you should check on. A machine with a lot of storage space is very fast as well. However, this machine may be very expensive. Data science tasks require no less than 1TB of storage space. Fortunately, you can buy an external hard disk if you cannot afford a machine with more storage space.