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Everything You Need to Know about the Best Laptop for Machine Learning

The need for Machine Learning is there and companies usually don’t pay much attention to the fact that any normal laptop that is being used by Software Developers and Support people are not suitable for Machine Learning.

To find the best Laptop for Machine Learning, Portability is one of the key factors that anyone looks for in a laptop, otherwise, if portability is not the issue then you can go for custom PC, which I’ll discuss in the later part of this article.

RAM: A minimum of 16 GB is required, but I would advise using 32 GB RAM if you can as training any algorithm will require some heavy Lifting.

GPU: This is the most important aspect as Deep Learning, which is a Sub-Field of Machine Learning requires neural networks to work and are computationally expensive.

The TensorBook by Lambda Labs would be my #1 Choice when it comes to machine learning and deep learning purposes as this Laptop is specifically designed for this purpose.

Pros: Great value for money, Superb performance with excellent thermal management, Value for Money Cons: The battery could be better

The Asus ROG Zephyrus S GX531GX is a stunning 15-inch gaming laptop that has the svelte design of an ultrabook but packs powerful GPU components.

The Dell XPS 15 is an amazingly flexible laptop, despite looking like an ordinary high-end one on the surface.

The MSI GS65 is once again, a thin and lightweight gaming laptop which is aimed for power users working on Deep Neural Networks.

Pros: Attractive, subtle design, Gorgeous, a fast display, Excellent performance, Effective thermal management Cons: Underside gets burning hot, Forthcoming Biometric login, Poor Native Audio

The Gigabyte Aero 15X is a fantastic laptop for tasks beyond gaming like Machine learning while maintaining its excellent battery life, making for a more versatile laptop than previous versions.

Edureka’s Machine Learning Certification Training using Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning.

This Machine Learning using Python Training exposes you to concepts of Statistics, Time Series and different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms.

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