Home Programming 5 Reasons Why You Should Undergo Training in Machine Learning with Python

5 Reasons Why You Should Undergo Training in Machine Learning with Python

What is Python?

Python is a multi-paradigm, high-level, general-purpose programming language that enables a clear programming structure on small, medium, and large scales. Created by Guido van Rossum and developed by the Python Software Foundation, Python supports procedural, object-oriented, and functional programming. It uses dynamic typing, reference counting, and a garbage collector for memory management. It is a highly extensible framework that also offers a choice in coding methodology helping you work quickly and integrating systems more efficiently.

What Is Machine Learning?

Machine learning is a subset of artificial intelligence. It studies algorithms and statistical models that are used by computer systems to learn without being explicitly programmed. Machine learning tasks are divided into many broad categories which include supervised learning, semi-supervised learning, unsupervised learning, and active learning. Machine learning includes many processes, techniques, and methods that can be applied to more than one type of machine learning algorithms like feature learning, manifold learning, sparse dictionary learning, anomaly detection, decision trees, and association rules.

Here are 5 reasons why you should opt for Machine Learning With Python Training.

1. Easy to grasp

Time and again Python has proven to be one of the simplest frameworks to master for new developers and users. The simplicity of Python helps developers understand the deep and complex algorithms of machine learning and deep learning in a way that they can focus on solving problems, rather than worry about the coding complications. Moreover, Python allows for faster development of applications because of its simple syntax that lets you test algorithms without much difficulty.

2. Low Entry Barrier

The Python programming language allows scientists and users to process data and information in the most convenient and effective way, with an added advantage of a low entry barrier. Users and developers find it extremely easy to use Python for AI development and machine learning because of its resemblance to an everyday English language which makes the processing of codes easy and efficient. More and more scientists, users, and developers are now shifting to Python because of its increased popularity due to a low entry barrier.

3. Pre-Built Libraries

The Python programming language provides its users with an abundance of pre-built libraries and frameworks that save coding and the overall development time by providing base level items so that developers don’t have to start from scratch, which in turn helps in their machine learning project. Moreover, the Python library lets you access, handle, and transform data for continuous data processing which is essential for machine learning. It also offers an option of PyPI wherein you can discover and compare more Python libraries. Libraries that are fundamentally helpful for machine learning offered by Python are:

  • Pandas: Allows merging, gathering, and filtering of data from external sources.
  • Keras: It uses the GPU in addition to the CPU for fast calculations and prototyping.
  • TensorFlow: Assists in working with machine learning and deep learning.
  • Scikit-image: Allows for image processing.
  • Scikit-learn: It is used in handling basic machine learning algorithms.
  • StatsModels: Assists in data exploration, and statistical algorithms.
  • Caffe: It is used to switch between the CPU and the GPU, together with processing 60 mln images a day.

4. Flexibility

The Python programming language is highly flexible in its approach offering ample benefits that include:

  • Option to choose between the object-oriented approach and scripting.
  • Option to associate different data structures together.
  • Offers a great advantage to developers who face difficulty in implementing algorithms by giving them an option to verify the majority of code in the IDE itself.
  • No need to recompile the source code when implementing changes.
  • Developers have an option to combine Python with other programming languages.
  • Works as a perfect back-end language.

5. Popularity:

Python with machine learning is becoming highly popular with each passing day because of the following reasons:

  • Allows for machine learning development on twenty-five platforms which include Windows, macOS, Linux, and Unix, etc.
  • Readability is extremely easy on the Python platform giving an option to every developer to change, copy or share their peer’s code.
  • The framework is backed by Google which offers reliability and efficiency to the developers.
  • The usage of big data and cloud computing solutions made it a dependable source for data science and is now increasing its popularity in implementing machine learning.

The machine learning with Python course offers huge advantages to new developers, enhancing their resume in the process and is a must for all aspiring developers

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