Top 6 Python Libraries for Machine Learning

          Python  has a vast number of Machine  learning  libraries  that are used to build a Machine learning model from scratch. All these Machine learning libraries are used for different tasks like computation, data preparation, data visualization and others, that needed to be performed for building Machine learning models. By using these libraries developers execute complex tasks without rewriting the code. Machine learning libraries are one of the reasons for the tremendous growth of Machine learning. In this article, we are going to learn about Python packages for Machine learning. So, let’s let started.

          We are going to learn about the top 6 Python packages for Machine learning. Below is the list of these libraries.

          NumPy is a Python library that is used for scientific calculations. It helps us to apply complex mathematical operations to our data very easily. In Machine learning, it is used for dealing with data in the form of metrics and arrays, also for applying mathematical operations to our data. It helps in improving the performance of the Machine learning model.

          To install NumPy on your machine use the following command in the terminal.

To read NumPy documentation click on this link.

          Pandas is the most powerful Python library for data cleaning and analysis purpose. It is an open-source library that provides simple data structure and data analysis tools. In Machine learning, it is used for data manipulation and analysis. 

          To install Pandas on your machine use the following command in the terminal.

To read Pandas documentation click on this link.

          Matplotlib is the most famous and versatile Python library for data visualization. It can handle both NumPy and Pandas data structures. For building a Machine learning model it is necessary to get insights into data and the best way to get the insights is in the form of graphs and other visuals. Matplotlib visualizes the data in an easy way that makes even complex data easily understandable.

          To install Matplotlib on your machine use the following command in the terminal.

To read Matplotlib documentation click on this link.

          Scikit-learn is the most  important  library in  Machine  learning. It helps Machine  learning  models to learn, transform and predict using data. It features almost every Machine learning algorithm. It offers wide applications for preprocessing, data splitting, model deployment, model evaluation and many more.

          To install Scikit-learn on your machine use the following command in the terminal.

To read Scikit-learns documentation click on this link. 

          TensorFlow is an open-source Python library developed by the Google Brain team in Google. It is a very strong and flexible Python library. It can be used for a wide range of Machine learning tasks but it focuses on building deep neural networks.

          To install TensorFlow on your machine use the following command in the terminal.

To read TensorFlow documentation click on this link

          NLTK is the most popular natural language processing library. It contains the most popular NLP techniques like tokenization, part-of-speech tagging, sentiment analysis and many more that make the task of NLP very easy and fast.

          To install NLTK on your machine use the following command in the terminal.

To read NLTK documentation click on this link

          Machine learning packages are one of the reasons for the growing popularity of Machine learning. Python packages for Machine learning are easy to understand and easy. Most of these packages are open-source that’s why we got new and better features very frequently which makes Machine learning easy to use. In this article, we covered the top 6 Python libraries for Machine learning and discovered how they are used for Machine learning.

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