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Best laptop for machine learning

What if you want to learn AI but don't know math? Part three. We assemble and configure the system

What if you want to learn AI but don't know math? Let's assemble and configure the system after having chose the best laptop for machine learning.

System Setup

Now let's get down to setting up the software.

You have three options:

  • Docker container
  • Virtual machine;
  • Clean install.
  • Docker

If you want to go this route, then you should start with the official Nvidia-Docker project. However, you still have to put a bunch of frameworks and libraries on top of this image.

Of course, you can also supply a container with everything you need for machine learning, for example, this one. Unfortunately, it has some unresolved problems, and it won’t fit on Dockerhub, so you will have to spend a lot of time on manual configuration.

Virtual machine

As I said at the beginning of the article, you can simply upgrade the hardware of your gaming computer, install VMware Workstation Pro that supports GPUs, and start working. This is the cheapest option, and very convenient to use.

First install

As a result, I chose this option. Yes, a little old school, but since I have been working as a system administrator for a long time, I decided to do everything manually – this way you can control the system as much as possible.

Let's first discuss a few details related to software. You will understand that most of the calculations are done using Python. In the future, this may change, but for now this is the main language. R and Scala are also popular, we will also consider them.

Here is a list of all the main packages that we will install:


  • Python 2.x
  • Anaconda (and Python 3.6) is a high performance Python distribution containing over 100 popular Python, R and Scala packages;
  • R – language and environment for statistical calculations;
  • Scala is a language similar to Java, but much more performant.
  • Drivers and APIs
  • Nvidia drivers;
  • CUDA is Nvidia's proprietary parallel computing platform and API model;
  • cuDNN is a library for Nvidia GPUs for working with deployable neural networks.

Helper apps

  • Jupyter is a great web application that allows you to share documentation and code.
  • Frameworks / Libraries
  • TensorFlow is Google's open source machine learning framework, which powers Google Translate, for example;
  • Theano is a popular machine learning framework;
  • Caffe is another framework;
  • Torch is a scientific computing framework that uses GPUs;
  • MXNET is a scalable machine learning system built by Amazon and several universities.
  • High Level Libraries
  • Keras is a high-level neural network library that runs on top of TensorFlow or Theano.
  • Lasagne is a lightweight library for building and training neural networks.

Python Libraries

A huge number of libraries have been written for various kinds of scientific activities, we will supply the most necessary ones:

  • Pip = package manager for Python;
  • Pandas = high performance data analysis library;
  • scikit-learn = popular powerful machine learning library;
  • NumPy = numerical Python;
  • matplotlib = visualization library;
  • Scipy = mathematical and scientific calculations;
  • IPython = interactive Python;
  • Scrappy = web scraping framework;
  • NLTK = natural language toolkit;
  • Pattern = web mining library;
  • Seaborn = statistical visualizations;
  • OpenCV = library for working with computer vision;
  • Rpy2 = interface to R;
  • py-graphviz = statistical graphs;
  • OpenBLAS = Linear Algebra.

HP ZBook Studio Laptop for Machine Learning

The HP ZBook studio was built for running complex calculations and applications. It has a powerful graphics processor that lets you create and run your data models easily. With 32 GB of RAM, your mobile computing system can simulate and build multiple projects simultaneously. With the HP Zbook studio, you do not need an external hard disk to save files.

Dell Inspiron 15

Even as the most affordable laptop on this list, the Dell Inspiron 15 is an excellent choice for machine learners engineers looking for budget laptops. Dell allows you to customize your laptop to suit your computing needs, as a way to optimize your funds. The tech specs for this laptop include an Intel Core i5 processor, a Windows 11 operating system, a 15.6-inch display size, good battery life, and 8GB of RAM storage space.