best processor for data science

7 Best Processors for Data Science and Machine Learning

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Are you a Data Scientist or looking to begin your journey, into the universe of machine learning, AI, and Deep-learning?

Do you seem to be pondering on what are the best CPUs for data science or machine learning, well we’ve just saved your time surfing and searching the internet by putting it all here.

Like tools are to a farmer or an automobile repairer, so is a suitable processor to a Data Scientist, they’re expected to be suitable for work and highly efficient.

It is common knowledge that not all processors would comfortably carry out the workload of Data Science, hence the need to be thorough and critical, once again a suitable CPU for a data scientist should be one with the ability to handle large data sets.

With lots of models and inventions making their way to the modern market, it gets increasingly harder to keep track of every processor that is been made, most especially for individuals looking to just begin their journeys, who are relatively new to the sphere. 

These are the various kinds of processors we’ve put together to make your decision-making process easier.

7 Best Processors for Data Science and Machine Learning


1. AMD RYZEN 9 3900X

What We Like:

Relatively low power consumption
Easy overclocking tools
Huge L3 cache

What We Don’t Like:

No integrated graphics

Released first in 2019, with a max RAM of DDR4-3200 up to 128GB, the AMD RYZEN 9 3900X is, without doubt, a processor with an overall high performance.

It is on this list due to its ability in handling large volumes of complex data, terrific in keeping intense workloads without running down your system.

With a hyper-threading feature that enables multi-tasking, the processor runs seamlessly even when handling multiple tasks, simply put, the processor could fish and drive at the same time…

On a lighter note, the hyperthreading features enable multitasking with 24 threads to simultaneously run your data without great struggle.

Also, the AMD RYZEN 9 3900X provides incredible overclocking possible speed offered by this model.

A notable spec is its large cache capacity, this is most ideal for professionals that deal with heavy data inputs

The RYZEN 9 is created to manage and economize power intake efficiently, it is natural for a processor handling that much data to overheat and consume a large amount of energy, it’s built-in handling such situations effectively. 

Though a bit expensive and on the high side, it however guarantees top performance, worth the price.


2. Intel Core i9 i9-9900k 

What We Like:

Unlocked Multiplier
Excellent for Multi-Threaded Applications

What We Don’t Like:

Quite expensive with a relatively low price to performance ratio.

First released date in 2018, with high-end CPU segment performance, 8 cores (3.6GHZ-5.0GHZ max turbo) a max ram of DDR4-2666 up to 128GB.

Supports overclocking and hyper-threading, making multitasking happen seamlessly without any hassle.


3. AMD RYZEN 7 3800X

What We Like:

Best Performance-price ratio
Bundled cooler
A solid blend of single and multi-threaded performance

What We Don’t Like:

Requires X570 motherboard for PCle 4.0

When you don’t want a crazy budget or looking to cut costs and still get good value for your money, then the RYZEN 7 38OOX is a good one to get.

The best price-performance ratio offers so much value for an affordable processor. It comes with its ultra-efficient and quiet AMD Wraith Prism LED RGB cooling system.


4. AMD Threadripper 3990x

What We Like:

Monstrous MultiThreaded performance
SingleThread improvements over 2nd gen
Excellent rendering performance
PCI Express 4.0 support

What We Don’t Like:

Requires new motherboards
Expensive

Launched February 2020, a desktop processor with 64 cores, 128MB of L3 cache, and at a speed of 2.9GHZ-4.3GHZ depending on the workload. Supports overclocking and comes with an unlocked base-clock multiplier.

It does have a flip side, the AMD Threadripper is power-hungry, consumes a lot of power, which requires top-notch cooling.


5. AMD RYZEN 5 5600X 6-CORE

What We Like:

very good heat management

What We Don’t Like:

high pricing

The AMD Ryzen 5 5600X is a desktop processor and based on the Zen 3 architecture.

Launched in November 2020, it is the fastest 6-core Ryzen desktop processor.

With a TDP of 65 watts, the Ryzen 5 5600X compared to other AMD families is the least power-consuming model in the Zen 3 family to date.

This processor’s 32 CPU cores and 64 threads make it an excellent alternative for individuals who cannot afford the Threadripper Pro 3995WX.

We must state that this processor is more than capable of handling the majority of machine learning and data science severe computations.

The Ryzen 5 5600X is clocked at a 3.7 GHz base clock and can be clocked up to 4.6 GHz with Precision Boost 2.


6. AMD Ryzen 5 2600 Processor

What We Like:

High Multiprocessing performance
Very Affordable
Good Temperatures

What We Don’t Like:

Lacks integrated graphics
Requires more core for higher performance

The most reasonable processor, a very favorable price in choice for machine learning or deep learning is the Ryzen 5 2600 processor coupled with the ability to work even with low voltages, it is equipped to work even with low power compared to most that are somewhat power-hungry.

The Ryzen 5 2600 has a key advantage as it can be overclocked to exceed 4 GHz on all cores.


7. AMD RYZEN 9 5900X

What We Like:

Great Value for the money
Good Temperatures
Very Affordable

What We Don’t Like:

CPU cooler not included

Without a doubt, this is among the best processor for data science, that will give you a greater value than the money you spend on it. Built on the Zen 3 architecture, 12 core, 24thread processor with a boost clock of up to 4.8ghz. The only thing to worry about would be power consumption which is sort of normal for most Ryzen products.

The Ryzen 9’s multi-thread performance may be one of its best features, with 12 cores and 24 threads.

FAQs

Is Ryzen good for Data Science?

They have a boost speed of 4.2–4.4 GHz and can handle even the most powerful GPUs, so one can say they are a favorable choice.

Is i5 enough for Data Science?

No straight answer to this, as there are various other specs that matter, generally an i5 would pose a degree of limitation to some volume of data processed, hence would not give a very satisfactory performance that a higher processor would give.

Gpu vs Cpu Deep Learning

GPU has been tested to run faster, in some cases 4-5 times faster. GPU is a better option in handling deep learning.

Intel vs AMD Machine Learning

AMD offers a higher price to performance ratio. Overall considering specifications, AMD is a better choice of CPUs for machine learning.


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