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Python is a dynamic language that supports object-oriented programming along with functional programming paradigms. It lets programmers complete the task briskly and efficiently. Students who are learning Python in their curriculum get hindrances in the form of bugs while doing Python assignments. This is when our online Python homework help service comes into the picture to complete your difficult tasks.
The best part about this language is the syntax, which is simple and quite expressive that allows the programmers to express their concepts in shortcodes. Python is also used as a scripting language in many non-scripting contexts. With the best memory management and dynamic type system, this programming language supports imperative and functional programming. The extensive libraries in Python allow programmers to run the code in different operating systems.
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Python offers a range of prominent features. A few of these features are:
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Following are the data science libraries that a student must know to work as a data science professional
It is one of the most important python libraries. TensorFlow library lets you do numerical calculations having around 3500 comments and a big community of contributors who can help you when you are stuck in the middle of completing the assignment on this library. TensorFlow is a framework that allows you to define and run computations that involve tensors. These are the computational objects that are partial and will produce a value. It produces graphics and cut down the errors in neural machine learning to 50 to 60 per cent.
It is an open-source Python library that is widely used in data science for doing high-level computations. It has many contributors on GitHub and can be used for extensive computations. It is considered an extension of the NumPy library. The library is user-friendly and allows you to efficiently do scientific calculations
It is the basic package that allows you to carry out numerical calculations in python and is considered to be a powerful N-dimensional array object. The array processing packages offer muti-dimensional objects, which are known as arrays, and tools to work with. It also addresses various problems by offering you multidimensional arrays, functions, and operators that will operate efficiently in arrays. It is widely used in data analysis.
It is part of the data science life cycle and is a popular library to be learned along with matplotlib. It is used for analyzing and cleaning the data. Pandas offer data structures, data frames that are designed to structure data. It is used for data wrangling and cleaning. ETL jobs will make use of this for transforming and storing data. It also supports CSV files as a data frame format.
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Python is the most preferred tool to code most Machine Learning and Data Science algorithms. Some of the most common algorithms where Python has applications are:
It is a popular supervised machine learning algorithm that observes the continuous features and predicts the outcome. It establishes the relationship between independent and dependent variables. If the model has a single predictor variable, it is called a simpler linear regression. When the model uses multiple predictor variables, it is called multiple linear regression. Linear regression is used to estimate the house cost, total sales, total calls etc based on the variables gathered.
It is another supervised machine learning algorithm that is widely used in Python and data science to estimate discrete values in binary. For example, true or false, yes, or no, and 0 or 1. It completely depends on a set of variables. The algorithm helps you to find out the probability of the outcome occurring by analyzing the data with the help of a logistic function or curve. Logistic regression is also known as the sigmoid function.
The decision tree is made by asking a lot of questions to part the data. The main purpose of using this decision tree is to partition the data at every level so that the model will have up-to-date information about the dataset. The model will pick a specific instance that traverses the decision tree by comparing various features with a conditional statement. When it goes to the left or right branch of the tree based on the result, the important features go closer to the root.
Random Forest is a machine-learning technique that helps you to resolve regression and classification problems. It makes use of ensemble learning as a technique to combine various classifiers to offer solutions to complicated problems. The random forest algorithm has many decision trees. The forest will predict the outcome based on the predictions that were made by the decision tree.
It is a type of machine learning algorithm that will make predictions about the best possible next model based on the previous models, thus reducing the prediction errors. It also sets a target outcome for the next model to cut down the errors.
It is a group of objects where the objects in the same group will have similar properties to the objects that are categorized in the other cluster. The categorization of clusters is done based on the distance, density of data points, graphs, and statistical distributions. It is widely used in statistics, machine learning, graph analytics, image processing, and social science apps.
It is a collection of neurons that will take the input and collects the information from the other nodes to come up with the outcome without using any programmed rules.
It is a type of machine learning and artificial intelligence that mimics humans to gain knowledge. Deep learning plays a critical role in data science. It also has predictive modeling and statistics. It is highly beneficial for data scientists to collect, analyze, and interpret huge data, and process that data quickly and easily.
It is a concept that is used to study social networks, fraud patterns, power consumption patterns, influence, and virality in social media. It is widely used in clustering algorithms, especially the K-means.
NLP is a widely used term in artificial intelligence. If you need help in writing an NLP assignment as part of your academic task, you can seek our programming expert's help. They write clean code with enough comments that help you understand the code and excel in the areas in which you are not aware.
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Here are a few real-world applications of Python on which most of the Python assignments and homework are based:
Python Data Science Assignment Help: It allows you to collect, sort, analyze and visualize data. The best functionalities available will deal with complicated mathematical calculations. The inbuilt libraries will offer enough convenience for data science professionals. A few of them include TensorFlow, Pandas, and Socket Learning. These libraries are used for data pre-processing, performing complicated data analysis, and fine-tuning the data models. We are here to take the burden of writing assignments off your shoulders. Submit your assignment with us now to avail Data Science Assignment Help.
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Web development using Python - It is the most widely used application of Python. There are various frameworks such as Django, Flask, Bottle, and so on using which you can develop web apps. It gives enough flexibility for developers to develop apps using the frameworks with ease. There are many tools and libraries available in these frameworks to make the whole process effortless. It offers the best visualization, easy development, enhanced security, and a quicker development process.
Game development using Python - Python is also used for developing games. Many popular games such as Bridge Commander, Caribbean, and so on are developed with Python. It offers a lot of functionalities and add-ons. There are also 2D and 3D gaming libraries available to develop games effortlessly.
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