ACTE is the most reputed Python Training that has mainly designed to give your career a strong boost in trending technology.Over the years Python programming has come across a long from being used for simple web development applications in the past to the present days highly advanced data analytics applications by Data Science. Python is also the backend programming language for most of the famous web & mobile applications.
Python is a highly popular object-oriented language which is simple to learn and easy to deploy as well. Python can easily run on various systems like Linux, Windows, and Mac. After the completion of Python Training, aspirants can easily work on Big Data Hadoop Environment for very high salary package range. Python is completely with Language Interoperability and documentation system with hierarchical module system to boost revenues.
Python is good for a career because it is valuable in the software industry for the following reasons: It is widely used you can easily assemble a team of programmers experienced in it. Recently Python Developer has become a very sought after job in the industry. ... Python programming language is much more preferred coding language than C++ and Java. This is because a Python code is not only shorter and more readable than its popular peers are but is also very versatile.
The future scope of python programming language can also predicted by the way has helped big data technology to grow. Python has been successfully contributing in analysing a large number of data sets across computer clusters through its high-performance toolkits and libraries. Salary varies as a Python Developer according to the different Cities in India. As per the present criteria, Bangalore is the number 1 city for working as a Python Developer. Therefore, the Salary in Bangalore is varied to 460, 000. In Pune, it is near about 320,000, In Hindi Its 220,000, New Delhi it is 120,000.
Python developers are in high demand - not only because the language is so popular and widely used but also mostly because Python became a solution in many different areas. From web applications to data science and machine learning. However, it is not enough to be master the language itself. s for Data Science, it is a rising star of the Python world. Pandas, Numpy and SciPy are all tools that are highly in demand, along with Jupiter notebooks.
We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings in Python. Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.
Yes, Python is valuable in a variety of different careers, not just as a programmer. ... If you want to become a software developer that utilizes Python, such as backend web development, Python is a great choice. It used in a variety of different areas. Yes, Python is valuable in a variety of different careers, not just as a programmer. ... If you want to become a software developer that utilizes Python, such as backend web development, Python is a great choice. It used in a variety of different areas.
The biggest difference between the two languages is that Java is a statically typed and Python is a dynamically typed. Python is strongly but dynamically typed. ... This makes Python very easy to write and not too bad to read, but difficult to analyse. Static type inference in Python is a known hard problem. Python is more productive language than Java. Python is an interpreted language with elegant syntax and makes it a very good option for scripting and rapid application development in many areas. ... Python code is much shorter, even though some Java “class shell” not listed.
Python is all about libraries- pre-written codes by the Python Devs/Community. All you have to do is to fetch these codes to make your own program(s). In short, it is great! Regarding your question, NO, one does not need to be proficient in C to learn Python. If you want to learn Python, you just need to know basics of programming languages like C and C++. ... Python has become the most popular language in year 2020. Once you learn Python thoroughly, it will become easy to find jobs. Many companies are using Python for developing their websites, GUI development.
Our courseware is designed to give a hands-on approach to the students in Python. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
However, the worth of any programming language totally depends upon the tasks to performed, or the field you are going to work it. After intense research, it has found that among all the programming languages, Python has enough reasons to be something worth to learn in 2020. It is always worth to learn programming language is popular and commonly used.... If you consider learning Python to get a job as a software developer, it seems a reasonable choice.
Python has managed to dominate other programming languages such as Java, C, C++, etc. ... In over the span of 25 years, Python has managed to reach a level that is high above others making it the fastest growing language. Not only this, but it also has a promising future along with the addition of other technology. The data science, AI and ML has more future for python in coming days with the salary hikes in India.
First and foremost reason why Python is much popular because it is highly productive as compared to other programming languages like C++ and Java. ... Python is also very famous for its simple programming syntax, code readability and English-like commands that make coding in Python lot easier and efficient... and there are some Top reason to learn Python.
Data science.
Scientific and mathematical computing.
Web development.
Finance and trading.
System automation and administration.
Computer graphics.
Basic game development.
Security and penetration testing.
Python will make you rich in the stock market!
There are so many factors involved in the prediction of stock market performance hence it becomes one of the most difficult things to do especially when high accuracy is required. Here data science & its techniques have been used to search patterns and insights that were not approachable before. Learning Python- object-oriented programming, data manipulation, data modeling, and visualization is a ton of help for the same. So, what are you waiting for? Read the complete article and know how helpful Python for stock market.
Stocker is a Python class-based tool used for stock prediction and analysis. (for complete code refer GitHub) Stocker is designed to be very easy to handle. Even the beginners in python find it that way. It is one of the examples of how we are using python for stock market and how it can be used to handle stock market-related adventures.
Understanding Stock Market Analysis
Stock market analysis can be divided into two parts- Fundamental Analysis and Technical Analysis.
a. Fundamental Analysis
This includes analyzing the current business environment and finances to predict the future profitability of the company.
b. Technical Analysis
This deals with charts and statistics to identify trends in the stock market.
Predicting Stock with Python
In this blog of python for stock market, we will discuss two ways to predict stock with Python- Support Vector Regression (SVR) and Linear Regression.
Support Vector Regression (SVR)
Support Vector Regression (SVR) is a kind of Support Vector Machine (SVM). It is a supervised learning algorithm which analyzes data for regression analysis. This was invented in 1996 by Christopher Burges et al. The cost function for building a model with SVR ignores training data close to the prediction model, so the model produced depends on only a subset of the training data.
SVMs are effective in high-dimensional spaces, with clear margin of separation and where the number of samples is less than the number of dimensions. However, they don’t perform so well with large or noisy datasets.
Linear Regression
Linear Regression linearly models the relationship between a dependent variable and one or more independent variables. This is simple to implement and is used for predicting numeric values. But this is prone to overfitting and can’t be used where there’s a non-linear relationship between dependent and independent variables.
Python for Stock market
Let’s look at the analytical capabilities of Stocker in parts.
Starting with Stocker
The first thing that should be done is importing the Stocker class into the current python session after installing the required libraries. You can use it to create an object. The constructed object will contain all the properties of the Stocker class. As the stocker is built on quandl WIKI database hence it allows access to 3000 and more US stocks.
Python classes are comprised of – attributes and methods. Amongst all the attributes of the class, one of it is stock data for a specific company.
The benefits of using the Python class include – the functions and the data it acts on are associated with the same object. The entire history of the stock can be plotted by using the method of the Stocker object. The ‘plot_stock’ function has a number of arguments that are optional and by default, it plots the adjusted closing price for the entire date range that can also be customized according to our needs (range, stats to be plotted, type of plot). Using ‘plot)stock’ we can investigate any number of quantities in the data present in any data range and also suggest real-world correlations.
Additive tools
These are very powerful for analyzing and predicting time series. We know that the long term trend of any established multinational company seems to be increasing in nature but there is a possibility of identifying yearly or daily basis patterns. Such help of time series with daily observations can be provided by Prophet, developed by Facebook. Stocker can do all the work that be done by Prophet behind the scenes using simple method call to create and inspect the model.
These types of models remove disturbance present in data and smoothen it. Prophet models also look into fluctuations of data in real-life processes and make predictions for the future. Though there is concern related to past data but future data analysis is what companies strive for. This method call returns two objects (data and model) which are then assigned to variables that are later on used to plot time series components.
Changepoints
It occurs when the time-series go from increasing to decreasing or vice-versa. These patterns are also very important as one needs to know when the stock rate is at its peak or there are significant economic benefits. Identifying these points and their cause of change helps in predicting the future. The stocker object can automatically predict the 10 largest changepoints which tend to line up near the peaks and valleys of the stock price graph (generally). On the other hand, the prophet can only find changepoints in the first 80% data only. Google search tools allow us to see the popularity of any search word over time in Google searches. Stocker can automatically retrieve this data for any specific term.