The data science field is growing at an incredible pace. More and more industries are turning towards data science to solve unique challenges.
Artificial intelligence is no longer something that is only used in the big tech companies but has become a part of everyday business operations.
Several tools and resources are required for conducting data science projects and artificial intelligence (AI) activities. To excel in the field of data science, one will also need to know about these technologies and how they can make these projects easier.
Data science and artificial intelligence are broad applications that address a common issue – solving problems through knowledge application.
In this post, you will find out about some of the best tech tools for data science and AI that can be used for professional use.
Scikit-Learn is a python library that is used for data mining, data analysis, and model building. This library is designed to operate with other python libraries like NumPy, SciPy, and Matplotlib.
TensorFlow is an open-source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them.
TensorFlow is a free artificial intelligence software library that was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization to conduct machine learning and deep neural networks research.
Numpy is one of the most popular python libraries used for working with arrays. It has the functions for working in the domain of linear algebra, Fourier transform, and matrices.
Py Torch is a python package developed by Facebook. It is an AI researcher’s open-source ML and deep learning framework.
Py torch provides a function for deploying mobile and embedded frameworks.
Keras is an open-source software library that provides a Python interface for artificial neural networks. It acts as an interface for the TensorFlow library. Keras runs smoothly on both CPU and GPU.
Theano is a Python library and optimizing compiler for manipulating and evaluating mathematical expressions, especially matrix-valued ones. In Theano, computations are expressed using a NumPy-Esque syntax and compiled to run efficiently on either CPU or GPU architectures. (Wikipedia).
DATA SCIENCE TOOLS
-Structured Query Language (SQL)
Statistical Analytical System (SAS) is a data science tool that is used for advanced analytics and complex statistical operations. Eg, data mining.
This is a programming language used for general programming and popularly used by data scientists and software developers.
-Microsoft Office Excel
This is one of the best and most popular tools for Data Science beginners. Excel offers various formulas for Data Science calculations like concatenation.
-Structured Query Language (SQL)
SQL is a recognized programming language for managing relational databases and performing different operations on the data contained within them.
SPSS (Statistical Package for the Social Sciences) is used to perform statistical data analysis. This tool also processes and analyze survey data in less time.
Matplotlib is an open-source Python plotting library that’s used to read, import and visualize data in analytics applications.
According to Wikipedia Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
The field of data science and Artificial intelligence is growing at an exponential rate and becoming more apparent every day.
The software and tools supporting this field are being packaged, marketed, and utilized by major corporations across the globe.
Many of these resources are free and readily available to anyone with a computer.
If any new tools are developed we will do our best to update you.