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| author | boostyslf |
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| permlink | how-did-i-learn-machine-learning-step-1-create-the-coding-environment |
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| title | "How did I learn Machine Learning : step 1 - Create the coding environment" |
|---|
| body | "Hi everyone, I am really passionate about studying and applying machine learning. A few years ago I have started to learn machine learning, therefore, I think that I have considerable knowledge of machine learning and I must continue on studying machine learning further. So I am starting the series of blog posts called "How did I learn Machine Learning" to distribute my knowledge on the machine learning. In this series of the blog post, I will provide you both theoretical knowledge and the example codes.
Since this is my first blog on steemit, please be kind enough to inform any mistakes done by me and any improvements you expect. In my future blog posts, I will try my best to address your suggestions. So let's start...
To become an expert in machine learning you need to thoroughly understand the theories, as well as you need to practice them by writing codes on your own. In my first blog post, I will give you a brief discussion on how to create a proper environment to start coding.
1. At present, most of the machine learning and artificial intelligence related projects are running on Linux based platform(I am using Ubuntu 16.04). The reason is that speed and manageability. Therefore I recommend you to use a Linux based platform to start with studying machine learning.
2. The next one is which language you should choose for coding. Python is considered to be in the first place in the list of all machine learning and AI development languages due to simplicity. So I recommend you to choose the python as the language for coding the machine learning related stuff.
3. When you are working with python, you need to manage the libraries which are used in your project/exercise. Most of the time one version of a specific library will not be compatible with some other version of another library. So you need to choose the correct version of the library and install it. This is a very annoying process if you install all libraries on the platform directly. Therefore you need a way to manage python libraries. For that, you can install anaconda. If you need to work with a specific set of libraries which are compatible together, you can create an environment and install those libraries into that environment. Now you can point to that environment and you can start on coding. By using these links you can learn how to install and learn on anaconda.
(https://docs.anaconda.com/anaconda/install/, https://www.digitalocean.com/community/tutorials/how-to-install-anaconda-on-ubuntu-18-04-quickstart)
4. If you are looking for a python IDE for coding I recommend you to install PyCharm. The community edition can be found here(https://www.jetbrains.com/pycharm/download/).
In this blog, I explained to you what is the environment you need to have to work with machine learning and this is the end of step 1. I will continue with step 2 soon. Please feel free to raise any concerns/suggestions on this blog post." |
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| title | "Welcome to Steem!" |
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Welcome to Steem @reggaecare. <br/><br/>Do read [A thumb rule for steemit minnows - 50:100:200:25](https://steemit.com/steemit/@steemladder/a-thumb-rule-for-steemit-minnows-50-100-200-25) for starter tips. <br/> <br/>Spend time reading [Steem Blue Paper](https://steem.io/steem-bluepaper.pdf) to know how Steem blockchain works and if you still have any queries ask them on our [Ask me anything about Steemit post](https://steemit.com/steem/@steemladder/there-are-no-dumb-questions-ask-anything-you-want-to-know-about-steem-blockchain) and we will try to answer that.<br/><br/> You can earn Steem rewards for reading and sharing your insights using our [Highlights Extension](http://bit.ly/highlights-extension)<br/><br/>All the Best!!!
</center>" |
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