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Which MacBook Is Best For Machine Learning?

02 Oct 2022

In today’s world, Artificial Intelligence has proved to be an emerging technology where creativity can be enhanced, productivity can be increased and business can be operate efficiently.

Lets take a look into Artificial Intelligence in deep. ‘Artificial Intelligence’ is a branch of wide range of computer science which is capable of performing tasks that require human intelligence and reasoning. In 1955, John McCarthy a computer scientist, first used the term “Artificial Intelligence” to define the intelligent machines.

Within a short period of time Apple introduced virtual assistant, “Siri” in year 2011. Now there are many examples of Artificial Intelligence: Siri, Alexa and other smart assistant, Self driving cars, Email spam filters, Netflix’s recommendations.

Machine Learning and Deep Learning are the subcategories of artificial intelligence. ‘Machine Learning’ refers to a type of AI that enables software applications that leverage algorithms and historical data to learn over time and predict likely outcomes.

Another subtype of AI is ‘Deep Learning’, which uses neural networks imitating the human’s ability to analyze the data and learn by identifying the patterns from a given dataset.

Apple has come up with new MacBook lineups such as MacBook Pro, MacBook Air, iMac, Mac mini. First macOS operating system was introduced in 2001, with the new interface.

It comes with in-built applications such as Pages, Numbers, Keynote, GarageBand. Apple shifted to Intel processor from PowerPC to increase its efficiency on 2005.

It has become the most powerful and efficient new Mac model and even more compact in size. As Apple wanted to make its own chip and was working on it for several years. Finally in June 2020, Apple confirm to move from intel processor to its new ARM chip (Apple Silicon chip).

In 2021, Apple introduced M1 Pro and M1 Max chip that delivers more powerful than M1 chip. Lets see which Mac Model fit best for Machine Learning and Deep Learning.

Some Basic Factors One Should Look After While Buying A MacBook For Machine Learning:  

Machine learning is a subset of Artificial Intelligence which consists of heavy and complex calculations. Deep Learning is a subset of Machine Learning and Nueral network are the backbone of learning algorithms.

Once the dataset is trained then it can predict the future behavior within few seconds. Here are some factors that we should look after while buying a suitable MacBook for Machine Learning purpose.

Portability, Handle Large datasets, Battery Performance, Price, Storage, Graphics card are the important factors one should look after:

Apple has also introduced M1 ultra chip yet not available in market so lets us talk about M1 Pro chip and M1 Max chip:

It is indeed a tough choice to say which M1 chip is better: M1 Pro or M1 Max? After the success of Apple’s M1 chip, there are significant improvements made in M1 Pro and M1 Max.

M1 Pro chip vs m1 max chip

M1 Pro chip:

M1 Max chip:

Personally I feel Apple M1 Max chip is more suitable for Machine Learning. Lets discuss more about it in detail:


Apple has tried to work very hard to built their own chip may it be M1, M1 Pro and M1 Max. Each of its chip are useful in various field but here we are particularly looking for Machine Learning.

In Machine Learning, the machine should be capable of handling huge and complex dataset and Apple MacBook Pro M1 Max chip has 16 core neural engine. It has one decode engine and two encode engine and two ProRes accelerators.

The price of Apple MacBook Pro M1 Max is higher than Apple MacBook M1 Max, but its a worth for one using it for Machine Learning. QuickTech offers special discount to their customers on every Apple Products so shop with us. www.quicktech.in