6 Important Python Libraries for Machine Learning and Data Science

1

• Session 1

2

• Are you planning to become a proficient and
  expert data scientist and machine learning
  expert? If your answer is yes, you must know
  about the different tools and technologies
  associated with it. For any individual who wishes
  to become an expert in data science and machine
  learning, they must know about the programming
  languages. There are several programming
  languages, but one of the languages that will
  help you a lot while pursuing and even
  implementing your knowledge in Python. If you are
  a beginner and are looking forward to the machine
  learning certification program, then you must
  consider taking the Python crash course, or you
  can join a full-time python learning course.
  Regardless of choice, you must be wondering why
  Python is so essential and the different Python
  libraries that will help you as data scientists.

3
Why is Python essential?

• You should not be surprised to know that Python
  is the most sought-after programming language and
  is considered to be the top-rated skill by
  universities and even industries. If you are a
  Python developer, then you may receive a salary
  up to 123,201 per year in the US, thus making it
  a lucrative career option. In addition to salary,
  Python is a highly versatile programming language
  that makes it useful across the different
  segments. Some of the areas where Python finds
  usage are
• Web testing
• Data extraction
• AI and Data Science research

4

• Multiple programming paradigms
• Web application and internet development
• Database easy access, faster system integration,
  and interface customization
• Cybersecurity
• Now that you know about the Python programming
  language, you must now focus on choosing the
  right platform for learning Python. Various
  institutes are offering Python certification
  programs. As a part of this learning, you will
  also learn about different Python libraries.
  Going ahead, we will discuss six important Python
  libraries, which you must know as a machine
  learning expert or data science expert.

5
Six popular Python libraries

• NumPy The first one that you need to learn is
  NumPy. This is the fundamental one, and various
  other Python libraries for ML are built on NumPy.
  As data scientists, you need to know about
  Python. Here are some of the uses of NumPy
• It has multi-dimensional arrays
• Linear algebra routines
• Random number generators
• Fast vectorized operations
• Comprehensive mathematical functions

6

• Pandas- It is the foundation library that finds
  usage in data analysis and manipulation. As a
  machine learning practitioner, one needs to work
  on the assessment filtering of a large volume of
  data. Handling large volumes all by themselves is
  difficult and may lead to errors, but with
  Pandas, you can overcome this. Panda is equipped
  to handle all this work and complete the job in
  less time without error. So, if you are going for
  machine learning for the beginner program, Pandas
  is going to help you a lot. You can use it to
• To write data between Python and other sources
  like the SQL database, CSV files.
• Data analysis based on descriptive statistics
• Manipulation and transformation of the data sets

7

• Scikit Learn (Sklearn)- It is a popular Python
  library for machine learning. It aids both
  supervised and unsupervised learning. It provides
  tools for fitting models, selecting, and
  evaluating models. It is built on NumPy and SciPy
  libraries. Key features of Scikit
• Fitting machine learning algorithms like
  clustering, regression, classification.
• Model evaluation
• Supporting machine learning pipeline integration

8

• NLTK- In addition to the above mentioned library,
  Natural language Toolkit is also an important
  Python library. It includes the following
  features
• Keyword search
• Text classification
• Named entity detection

9

• SciPy- The next Python library that makes our
  list is the SciPy. It is used for advanced
  mathematical operations on NumPy data. Some of
  the key features of SciPy are
• Optimization
• Fourier transforms
• Signal processing
• Probability
• Statistics

10

• Keras- The last one that we will be highlighting
  is Keras. It is used for building neural
  networks and modeling. This is very easy to use
  and thus becomes one of the most popular Python
  libraries amongst the machine learning
  practitioners. In addition to the extensibility
  that this Python library has to offer, it is
  Microsoft integrated CNTK (Microsoft Cognitive
  Toolkit) that serves as backend. If you wish to
  experiment using compact systems, then this is a
  great tool, to begin with.
• There are various other libraries that you can
  find, and can also learn. Most of the ML
  certification program is going to help you get
  actionable knowledge on these concepts. Once you
  have knowledge of Python libraries, machine
  learning, and data science applications, it will
  be a cakewalk.

11
Conclusion

• Global Tech Council is one of the leading
  platforms offering an online certification course
  in machine learning and data science
  certification, and if you too wish to become an
  expert in this domain, this is the right time to
  start your machine learning certification
  journey.

12
(No Transcript)