Exploring Python Ecosystem for Machine Learning: Things you should know
Machine Learning Episode : 1 Numpy, Pandas, Keras, TensorFlow, Scikit-Learn, MatPlotlib,NLTK with Coding Examples.
Make a way for the most generic intro of python programming language. In order to get into Machine Learning Ecosystem, you need to have some basic understanding of Maths (as we have discussed in an earlier episode ) and now we are going to introduce you various python library that are very useful for M.L, Deep Learning, and AI.
Python is a High-Level scripting language. If you want to make a career in the domain machine learning you need to know python programming.
But, Why Python?
Well there are many reason,
- Huge library support.
- Easy to understand and Powerful to execute.
- Fortune Companies admire python coders.
- Easy learning curve.
I’m going to list out few libraries based on python programming that is very useful for Machine Learning or AI.
# 1. Numpy
It is a Python library that provides a multidimensional array object, including mathematical, logical, matrix manipulation, sorting, I/O, discrete Fourier transforms, basic linear algebra, basic statistical operations, random simulation and much more.
#2 Pandas
It’s open source library for python programming languge for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series.
#3 Theano
Theano is a numerical computation library for Python. In Theano, computations are expressed using a NumPy-esque syntax and compiled to run efficiently on either CPU or GPU architectures.
#4 Tensorflow
TensorFlow is a Machine Learning framework created by Google for creating Deep Learning models. Deep Learning is a category of machine learning models that use multi-layer neural networks.
#5 Keras
Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation.
#6 Matplotlib
Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy.
#7 Scikit Learn
Scikit-learn is a machine learning library for the Python programming language.It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.
#8 NLTK
NLTK a.k.s Natural Language Toolkit is a platform for building Python programs to work with human/natural language data. It provides easy-to-use interfaces to corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries.
Done! This was the Foundation ML library that you should know before you get into the ML or AI Ecosystem. Practice this thing and get supercharged.
See you in the next episode of Machine Learning. Soon I’m going to share my github repo so that you can have access to the code.
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and as always thanks for Reading!.
