How Have Python Made Machine Learning Convenient?

25 April 2019

In the world of software development, Machine Learning also known as ML and Python are the two most popular terms that are in the current craze. Python is a high-level software programming language that has become the underlying base of many famous applications like Nextdoor, Instagram, etc. Machine Learning is a very important part of Artificial Intelligence (AI). Both of them target towards improving the many aspects of computer applications in their own different ways. Python is a programming language that is extremely easy to understand because of its simple syntax structure. As a result, developing the applications becomes a quite easy and simple yet strong framework. Machine Learning, on the other hand, helps an application to self-improvement without any prior programming.

Integration of Python with Machine Learning has offered a number of benefits to the candidates because of which, candidates are able to work in this field more conveniently and efficiently. In order to understand how Python has made things convenient for the individuals, it is important to understand the various facilities of machine learning with Python.

How Have Python Made Machine Learning Convenient?

Ease of Understanding:

As discussed above Python is one of the simplest forms of programming applications. Since, Machine Learning consists of complex algorithms, having one easy language to form the structure increases the code readability and decreases its maintenance.

Vast Libraries:

The huge volume of libraries that are available in Python for Machine Learning’s disposal is simply amazing. Some of the famous libraries are Numpy and SciPy for respectively for scientific computation and advanced ones. Data Analysis and Mining heavily rely on SciKit- learn. One framework named PyTorch is specially developed for Machine Learning. Other popular frameworks include Apache Spark, CNTK, TensorFlow, etc.

Better quality output:

Python is easy to understand and develop leaves the developers with plenty of time to increase the quality of Machine Learning application. The trial and error time on the complex algorithms is much less thereby providing plenty of space for improvement. The result of such an effort is usually very satisfying providing the end user with a pleasant experience.

Extensive Support:

The community of Python and Machine Learning Developers is ever increasing. In case, one stumbles in any area for their development, there is a horde of solutions available that are provided by the members of this huge community. Help is just a click away for any issues that one encounters during the course of development

Flexibility:

The flexibility the Python provides in developing frameworks for Machine Language is just amazing. The numerous approaches that can be used in development are lucrative for the designers and the developers. Linking data is altogether quite different becomes very easy for Python based Machine Learning frameworks.

Name and Fame:

The popularity of Machine Learning with Python base is on high demand. As a result, more and more people are inclining to learn and use the combinations. Therefore, it is easy to get such trained individuals in the market and get the job done.

Higher Career Opportunities:

In the hindsight of the previous discussion, more and more companies and organization are changing their base towards Python based Machine Learning frameworks. Therefore, job opportunities are increasing. This results in getting better jobs where the pay is extremely good and rewarding.

Fewer Trials and Tribulations:

Since Python has such a huge number of libraries, there is no practical need to compile the language in the instructions of the Machine Learning beforehand. It can be directly used in the program. Needless to mention, it saves time and effort which the two essential factors in any development and delivery.

Cost Saving:

It is a known fact that Python is an open source language that can be used freely in the system without any licenses. This aspect saves a huge amount of money that is otherwise spent on licensing fees across numerous platforms. The cost saving is immense which increases the budget of the project thereby increasing the quality in general.

Dynamic Support:

Machine Learning is a fast-paced framework that needs dynamic support. There are very less number of high-level programming languages in the current market that can provide such support, except that of python.

Platform That Is Quite Independent:

The flexibility that Python provides urges the developer to use it in any Machine Learning platform. This independence of platform that can be seen in the case of Python is making it extremely handy for a Machine Learning project that leads to successful development.

Statistical Modeling:

The model that can be used to develop a Machine Learning framework can be many. Python helps to create statistical modeling for the Machine Learning that is easy to comprehend and maintain.

Data Set Maintenance:

The first step towards developing a successful Machine Learning framework is to maintain a strong data set. Data set can be defined as a collection of information that the Machine Learning uses to enrich its algorithms. Using Python to set up the data set for Machine Learning is extremely easy and hassle-free.

No Learning Hassles:

As previously mentioned Python is easy to understand. This causes no learning hassles for individuals. Therefore, creating able developers with Python knowledge for Machine Learning frameworks becomes quite easy and less time-consuming.

Easy Transition in Research:

The machine learning frameworks that are primarily developed for the research projects rely heavily on Python as their base. Research projects related to pattern recognition or data analysis do not have enough time or budget for complex development languages. In such scenarios, Python provides the best solution with its ease of understanding and easy comprehensiveness.

Customization Is Quite Convenient:

Python’s flexibility with its easy to understand programming syntax and platform independence actually helps it to be customized to any need. A solution fits in all the needs and requirements without much hassle.

Highly Adaptable In Nature:

Python is a programming language that is quite easy to comprehend. The range of its comprehension is on a global scale. Even a fourteen-year-old kid would be able to understand and code in Python. This aspect increases its adaptability in the numerous Machine Learning platforms that are widely used across various areas.

No Space Crunch:

Machine Learning is all about efficient data handling and the way an application with the use of available data can do a better performance without any human intervention. This requires a lot of server space to load various kinds of data to feed into the respective algorithms. Python’s easy code requires much less space as compared to others. Therefore, it saves precious server space to accommodate more data thereby increasing the Machine Learning performance.

Conclusion:

The rising popularity wave of Python and Machine Learning will not go away that easily. Therefore, it is high time that both these aspects should be learned and implemented. Learning them would open different doors for numerous opportunities. Python because of its easy comprehensiveness will be the only weapon to code Machine Learning in the near future. It is always advised to future ready with an enhanced skill set.

Machine Learning will slowly have a huge impact on the world we live in. Understanding and controlling machine learning would be the only way to survive in the cutthroat competition. Using the weapon of python one should start conquering the area of Machine Learning. It is the best buddy that developers want to be friends. The benefits would be extremely rewarding when one integrates the programming language of Python with the various aspects of Machine Learning framework.

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Ariana Smith

I enjoy writing and I write quality guest posts on topics of my interest and passion. I have been doing this since my college days. My special interests are in health, fitness, food and following the latest trends in these areas. I am an editor at Content Rally.

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Are you looking for a service that can help you to make a web design, graphic design or graphic illustration, mobile and web application development, video production or animation, or anything that can support the marketing strategy of your business? Then, it is worth to consider FuseLab Creative. Have you ever heard about it? If you have not, here are the reasons why you should try their services. What is FuseLab Creative? FuseLab Creative is a design firm or design agency which is specialized in UI designs, UX designs, illustrations, and many more. The main services of this design company are UI designs, UX designs, web designs, mobile and web app development, graphic design or illustration, marketing and communications, video production or animation, and VR or AR. This design agency is one of the best in the Washington DC area. They believe that the core of a successful campaign, application launch, or web design, is creative skills as well as mad science. Some of their best ideas come from their programmers. While their most innovative code concepts come from their creatives. FuseLab Creative really use the lab environment, the place where they keep experimenting to stay ahead of trends. They apply the most memorable strategies on behalf of their clients. So, it can be assured that you will not be disappointed by this design firm. FuseLab Creative focuses on creating a memorable and impressive experience on behalf of their clients. Their core mission is creating positive memories. What Do They Do? FuseLab Creative believe that one thing to understand marketing and communication's principles and tools is an entire another universe to attract the type of attention with messages or designs that really impact behaviors. They believe that the core of this industry is what they call as a creative science. And with that creative science, they purpose to create impressive memories and experiences on behalf of their clients every day. When it comes to web design, FuseLab Creative thinks that it should be like a communal meeting place for clients. The clients should feel like they are being understood as well as attracted to find out more. Whether you sell a service or a product, or you just want to be noticed in a crowded marketplace, FuseLab Creative always tries to create a strong relationship between their clients and what they serve. However, every single one in this design firm keeps looking for a better formula since this kind of relationship keeps evolving. This shows how dedicated this design firm is. Things are the same when it comes to their application development services. The application team of FuseLab Creative is like a problem solver. You are able to always rely on them. This design agency is awarded by the Behance members. It ranked in number 2 as the most appreciated creative field of UI design and UX design. And it ranked in number 3 as the most appreciated creative fields of all creative fields. Are you interested to use their services? Read Also: Tips On Building Your Resume For A Website Design Company Discuss With Your Web Designer And Explain What You Want Before Starting The Job

Tech Challenge for Lenders – UMDP Data Standardization to Aid Closing

The mortgage industry overhauled its processes and technologies with the TILA/RESPA Integrated Disclosure (TRID) Act rolling out. Technology initiatives that created competitiveness between banks soon became the norm. Compliance needed to move north. Now, automation has made paperless mortgage a reality with loan origination software, retail point of sale, customer-direct solutions, and electronic documents providing complete end-to-end support. Regulations are constantly changing and lenders, still in their TRID hangover, need to do more. What is UMDP? In the pre-recession era (before 2008), borrower and loan information was sourced and stored by different agencies. Siloed information hindered different players from accessing true data and it was usually shared by email. This resulted in errors and insufficient access to data in the banking system. Uniform Mortgage Data Program (UMDP) is the last leg to the realization of the electronic mortgage. Just as TRID brought in enhanced data quality in the origination, UMDP will improve data standards in closing disclosures and data interpretation. Government-sponsored enterprises (GSEs) have indicated, come 2017, they will refuse to buy loans that fail to conform to the Uniform Closing Dataset (UCD) standard. The Federal Housing Finance Agency (FHFA) is directing government-sponsored agencies (GSEs) to create a common approach, protocol, and data set for mortgage data. The common data set, which is understood by all, will improve data accuracy. Definition ambiguities of loans purchasable by GSEs can be avoided. The lenders can capture granular data of a particular standard. The Uniform Collateral Data Portal (UCDP) will be one electronic portal through which all lenders can submit appraisal data. The Uniform Appraisal Dataset (UAD)will provide common definitions and requirements of appraisal data. The Uniform Mortgage Servicing Dataset (UMSD) will define the data set with standardized definitions, formats, and values. The Uniform Closing Dataset (UCD) will provide standard data for the closing disclosure form. UMDP may have bestowed the entire industry with mortgage data becoming uniform and accurate, but the upgrades rigmarole still worry lenders. However, GSEs have chosen to be capable of verifying underwriting data and audit data anytime. Customer preference lies with a seamless closing process and the impetus for lenders will be to transition into e-mortgage. Fannie and Freddie have already announced that they will purchase loans if the appraisals were submitted electronically and met the UAD standard. Technology vendors are already ensuring that their solutions transform appraisal information into data compliant with the Mortgage Industry Standards Maintenance Organization (MISMO). Manual processes are slowly fading and lenders are going to cloud-based mortgage origination and servicing software. The entire process needs to be seamless to ensure compliance from origination to closing. Today, the challenge for loan origination software is compliance, but tomorrow the focus will be imminently on collaboration. It will be important to have data which can be shared and understood by all. Standardization helps loan originators and customers to access data from diverse sources and interpret them effectively. Data standardization is the key driver for e-mortgage and paperless origination and closing. UMDP will be the “new normal” and help the industry to standardize their processes for better visibility and faith in the system. Preethi vagadia is a business architect worked in Mortgage and Finance software department with top notch companies and has over 8 years of experience in Mortgage Lending Technology,Mortgage Technology software, mortgage management software, etc. She has also worked on several process improvement projects involving multi-national teams for global customers in warranty management and mortgage.

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The academics Mrudula Joshi and Latika Gupta have defined infographics as, “pictorial representations of information intended to disseminate information quickly and clearly”. Additionally, they state that the quality of an infographic is determined by its content and its visual appeal. Infographics are a useful way of conveying information visually and can be used in a wide variety of applications. Businesses often use infographics to convey information to their employees, shareholders, and the general public. Infographics use the language of visual media to convey information in a manner that is unique and can transcend language. This allows infographics to be very accessible which helps businesses convey information efficiently and effectively. Checkout Ten Best Infographic Examples In 2022: This article will analyze 10 of the best examples of infographics in 2022 and discuss the effectiveness of the infographics' use of visual language to convey information. 1. Wyoming LLC Attorney: Everything Owned by Nestlé This infographic breaks down the considerable number of brands that are owned by the multinational giant Nestlé. Through its use of simple outlines, it separates the brands into their different industries which makes visually reading the information easier. This also conveys the message behind the infographic which is that Nestlé’s brands are overwhelming the market and are not competing with each other but with brands that Nestlé does not own. 2. World Resources Institute: The Carbon Budget Source: World Resources Institute This infographic explains the carbon budget and its implications for society. This is a complex topic and it is effectively handled through a well-designed pathway that guides the reader through the infographic. This pathway is constructed in two ways: firstly the line which runs throughout the infographic and secondly through the gradual lightening of the background color. 3. World Bank: Climate Extremes, Regional Impacts, and the Case for Resilience This infographic illustrates the increasingly prevalent effects of global warming on people and places in Africa and Asia. The infographic uses color in a particularly effective manner. The orange and yellow hues contrast pleasantly with the shade of blue. Color psychology informs us that blue as a color evokes emotions of trust and orange evokes emotions of friendliness. The infographic uses both colors to create a welcoming but informative tone. Source: World Bank 4. Valentina D'Efilippo: Poppy Field Source: Valentina D'Efilippo This infographic uses the icon of the poppy to visually illustrate the number of deaths that have occurred during major conflicts since 1900. The size of the poppy represents the number of deaths that have occurred and the length of the stem represents the duration of the conflict. This is a visually striking infographic that creatively expresses statistics in a truly artistic manner. 5. Udacity: How to Pick Your First Programming Language Based on the Life You Want Source: Udacity This infographic breaks down the programming job market by programming languages as well as gives beginner programmers a better understanding of the application of different programming languages. The infographic uses a pleasant yellow background and subtle pops of color to distinguish between the different programming languages. This allows the reader to immediately know which language is being discussed without needing to check each time. Additionally, the infographic uses creative graphs which are both informative and aesthetically pleasing. 6. Arnav Sameer: The Six Principles of Design This infographic dissects the six principles of design and the individual components which make up these principles. The infographic utilizes the elements of design that it discusses to enhance its visual appeal. This is satisfyingly coherent and it drives home the message of the infographic. Additionally, the use of color is very limited but this only serves to enhance the aesthetic of the infographic. Source: Folography 7. Juan Martinez: History of Life Source: Juan Martinez This infographic presents the history of planet earth and life as we know it. It includes the different time periods of the earth as well as the positions of the continents and how they have shifted over time. It uses a strong circular design to draw the reader's eye to the center of the infographic. Additionally, further information is presented in a clear way that relates back to the central image. 8. Venngage: Netflix Font Psychology Source: Venngage This infographic analyzes the font that popular Netflix shows use for their titles. It breaks down the different categories of fonts and what these fonts say about the shows as well as their audiences. The infographic utilizes an almost black background to make its limited use of color particularly emphatic. This also functions as a means of placing a great deal of emphasis on the white text which reveals the font each show decided to use. 9. Dorothy: A History of Hip-Hop Source: Dorothy This infographic charts the history of the hip-hop movement using the style of a blueprint. It emphasizes the artists which have had the most significant cultural impact on hip-hop and link these artists to other prominent figures of the hip-hop movement. The design of the infographic encourages exploration of its intricacies through a web of interconnecting lines and bold use of only two colors. 10. Rick Slusher: The Architecture of Inception Source: Rick Slusher This infographic condenses the complex plot of the film Inception into a digestible and visually striking piece of media. Each line represents a character and the warped layers of the central shape represent the layers of dreaming that the characters experience. This infographic proves that almost anything can be represented visually in a clear manner, even something as convoluted as the plot of Inception. Final Thoughts This list has compiled the best examples of infographics and illustrated how diverse and creative the medium of infographics is. Each infographic manages to condense a great deal of information into an easily digestible and visually appealing piece of media. The use of infographics is tremendously diverse and these infographics demonstrate the manner in which the medium can be used for any number of purposes. Read Also: Is Instagram Algorithm Easy To Beat?5 Benefits of Digitalization in MarketingLatest Trends of Graphic Design in London

How Have Python Made Machine Learning Convenient?

How Have Python Made Machine Learning Convenient?

Ease of Understanding:

Vast Libraries:

Better quality output:

Extensive Support:

Flexibility:

Name and Fame:

Higher Career Opportunities:

Fewer Trials and Tribulations:

Cost Saving:

Dynamic Support:

Platform That Is Quite Independent:

Statistical Modeling:

Data Set Maintenance:

No Learning Hassles:

Easy Transition in Research:

Customization Is Quite Convenient:

Highly Adaptable In Nature:

No Space Crunch:

Conclusion:

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I enjoy writing and I write quality guest posts on topics of my interest and passion. I have been doing this since my college days. My special interests are in health, fitness, food and following the latest trends in these areas. I am an editor at Content Rally.

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