BENEFITS OF PYTHON

Python is a widely used high-level language for general-purpose programming.Apart from being open source programming language,python is a great object-oriented,interpreted and interactive language.Python combines remarkable power with very clear syntax.It has modules, classes, exceptions,very high level dynamic data types and dynamic typing.There are interfaces to many system calls and libraries,as well as to various windowing systems.New built-in modules are easily written in C or C++(or other languages,depending on the chosen implementation). Python is also usable as extension language for applications written in other languages that need easy-to-use scripting or automation interfaces.

Machine Learning

Machine Learning is simply making a computer perform a task without explicitly programming it.In today's world every system that does well has a machine learning algorithm at its heart.Take for example Google Search Engine,Amazon Product recommendations,LinkedIn,Facebook etc.All these systems have machine learning algorithms embedded in their systems in one form or the other.They are efficiently utilizing data collected from various channels which helps them to get a bigger picture of what they are doing and what they should do.

Python is widely considered as the preferred language for teaching and learning ML(Machine Learning) because :

1. Simple to learn.As compared to C,C++ and Java the syntax is simpler and Python also consist of lot of code libraries for ease of use.
2. Although it is slower than some of the other languages,the data handling capacity is great.
3. Open Source !- Python along with R is gaining momentum and popularity in the Analytics domain since both of these languages are open source.
4. Capability of interacting with almost all the third party languages and platforms.

Deep Learning

Deep Learning is a class of Machine Learning algorithms that uses multiple layers to progressively extract higher level features from the raw input. For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters or faces.

Smart developers are choose Python as their go-to programming language for the myriad of benefits that make it particularly suitable for Deep Learning projects because of its simple syntax and readability promote rapid testing of complex algorithms, and make the language accessible to non-programmers

Advanced Analytics

Advanced Analytics is a part of Data Science that uses high-level methods and tools to focus on projecting future trends, events, and behaviors. Data mining is a key aspect of advanced analytics, providing the raw data that will be used by both big data and predictive analytics.New big data technologies enable cost-effective storage, processing and analysis of large amounts of data Modern and intuitive user interfaces allow more user groups to draw insights and make informed decisions, and Advanced Analytics software enables better analysis, and analysis of relationships and future events.

Pandas is the Python Data Analysis Library, used for everything from importing data from Excel spreadsheets to processing sets for time-series analysis. Scilkit-Learn and PyBrain are machine learning libraries that provide modules for building neural networks and data preprocessing.

Predictive Analytics

Predictive analytics is the branch of the Advanced Analytics which encompasses a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events.

Exploration and Data Analysis

Exploratory and Data Analysis is a phenomenon under data analysis used for gaining a better understanding of data aspects like,main features of data,variables and relationships that hold between them.The goal of Exploratory Data Analysis is is to obtain confidence in your data to a point where you’re ready to engage a machine learning algorithm. Another side benefit of EDA is to refine your selection of feature variables that will be used later for machine learning.

Data Science

Data Science is the study of data.It involves developing methods of recording, storing, and analyzing data to effectively extract useful information. The goal of Data Science is to gain insights and knowledge from any type of data both structured and unstructured.

Pandas from Python Library, used for everything to import data from Excel spreadsheets to processing sets for time-series analysis. SciPy is the scientific equivalent of NumPy, offering tools and techniques for analysis of scientific data. Statsmodels focuses on tools for statistical analysis.

Statistics

Python is a general-purpose language with statistics modules. R has more statistical analysis features than Python, and specialized syntaxes. However, when it comes to building complex analysis pipelines that mix statistics with image analysis, text mining, or control of a physical experiment, the richness of Python is an invaluable asset.