TOP 10 MACHINE LEARNING TOOLS 2021

 

Here is the list of the top 10 machine learning tools in 2021.

Machine learning (ML) is one approach for businesses to improve how they use large data to better understand their consumers’ behaviour, happiness and loyalty. ML can look for patterns and abnormalities that users wouldn’t think to look for on their own.

Some machine learning algorithms are pre-programmed to specialise in a certain task, but in this article, we’ll focus on machine learning tools that allow users to create their own machine learning methods for any data they have. Now, let’s get down to the top 10 machine learning tools of 2021.

 

Best Machine Learning Tools

Shogun

Shogun toolbox, often known as Shogun, is a machine learning tool library that is independent and accessible to use. The solution is written entirely in C++, making it highly accessible to enterprises of various sizes and backgrounds. Shogun is also available in a number of other programming languages, like R, Python, Ruby, Scala and others.

Shogun includes a number of methods and data structures that may be used to investigate typical machine learning issues. This programme may be used to add vector machine functionality to an existing tool or to play around with clustering techniques and linear discriminant analysis. Advanced user interfaces make learning and evolution simpler.

 

Scikit-Learn

Scikit-Learn is a machine learning package developed as a single platform, which is an intriguing strategy for machine learning software. This technology may be used for a range of data management and building strategies. Scikit-data Learn’s regression, categorization, clustering, and pre-processing capabilities and also the ability to acquire other Python modules, are popular among its users.

Apart from allowing you to manage and manipulate your data in a variety of ways, this technology may also assist business executives in the development of Python-based machine learning methods. You may also use the same environment to test and train your algorithms.

 

Jupyter Notebook

Jupyter Notebook is one of the most well-known machine learning software programmes available. The solution combines ultra-fast processing rates with an easy-to-use platform for developing and learning. Furthermore, developers have the option of working with one of three languages: Python, R, or Julia.

Jupyter offers a large community of developers from all around the world as an open-source solution for MI and computational applications. The Jupyter notebook allows you to share and save live code while working on your projects, then access technology via a graphical user interface.

 

WEKA

WEKA was created at the University of Waikato in New Zealand and is also known as the Waikato Environment for Knowledge Analysis. This tried-and-true open-source machine learning system may be used via a graphical user interface, a Java API, or conventional terminal programmes. While WEKA has a wide range of uses, it is most often used for research, teaching I models and developing robust applications.

WEKA is ideal for novices since it has a variety of built-in tools for developing machine learning jobs. You may also receive complete access to a number of other well-known toolboxes, such as Sckit-Learn.

 

Azure Machine Learning Studio

Azure Machine Learning Studio has been one of the earliest drag-and-drop technology solutions for machine learning algorithms, created by Microsoft. The Azure portfolio now includes a far larger collection of machine learning tools, such as the Machine Learning Designer, which streamlines and speeds the process of developing, testing, and maintaining machine learning models.

The Azure Machine Learning Studio is a simple-to-use application that assists businesses in connecting modules and datasets into a plan for developing machine learning technologies. GPU and CPU access are also supported by Azure.

 

KNIME

KNIME specialises in everything from statistical analysis and administration to deep learning research, with the goal of making innovation more accessible to the general public. Businesses may use KNIME software to access data from multiple touchpoints around the organisation and combine it into actionable insights. You may utilise data technology to make sense of your statistics, then use that knowledge to inform your machine learning algorithm.

KNIME is a GUI-based machine learning tool that is completely open-source. To get started with this service, you don’t need any programming experience. Anyone can start mining their data and making the most of it.

 

Amazon Machine Learning

The Amazon Machine Learning software intends to provide any developer and data scientist access to machine learning capabilities. The platform, which was recognised a leader in Gartner’s Magic Quadrant for AI developer services, is assisting businesses of all sizes in rediscovering what’s possible in the ML world.

Companies may use this technology to swiftly construct, train and deploy multiple machine learning services, integrate AI into existing systems, or create custom solutions based on their company’s specific needs. There’s a lot of help available to get you started, as well as a variety of deep learning frameworks and machine learning infrastructure alternatives to select from.

 

Google Cloud AutoML

Google’s Cloud AutoML solution, being one of the most affordable machine learning software solutions available, allows even developers with minimal AI experience to develop high-quality machine learning methods. Through pre-trained models built to support diverse services, such as speech and text recognition, this integrated technology gives any organisation the potential to reap the maximum benefit of artificial intelligence.

 

RapidMiner

RapidMiner is a machine learning platform for executives, data scientists and forward-thinking businesses. RapidMiner, which is now used by over 40,000 firms across the world, lets businesses tap into their valuable information and turn it into applying machine learning.

RapidMiner users may use visual workflow designers, automatic modelling tools and extensive data discovery and preparation tools to access a range of machine learning techniques. There are also applications in almost every industry!

 

TensorFlow

TensorFlow is a popular name in the machine learning field, presently owned by Google. TensorFlow, like many other popular software alternatives, offers an open-source framework that is ideal for large-scale machine learning applications. It combines deep neural networks with other machine learning techniques and it’s very useful for Python users.

The fact that TensorFlow can operate on both CPU and GPU technologies is maybe its most essential feature. There are also a plethora of models and datasets to explore, including support for natural language processing, picture classification and more. TensorFlow has also just launched a certification scheme of its own.

 

Conclusion

The demand for intelligent technology is greater than ever as the globe undergoes a tremendous digital change. However, there are a variety of excellent software programmes and tools available for leaders who want to take advantage of this environment.

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TOP 100 ARTIFICIAL INTELLIGENCE STARTUPS TO LOOKOUT FOR IN 2021

 

Sooner or later, the concept of digitization will completely take over all repetitive tasks. Today, with the help of big data, advanced technologies like automation, artificial intelligence, IoT, and machine learning are leveraging unimaginable amounts and types of information to work from. It is streamlining tedious, repetitive, and difficult tasks, which tend to slow down production and also increases the cost of operation. Owing to the evolution of technology, artificial intelligence startups are mushrooming like never before. The companies are driving the world into a new phase of digitization with a mixture of disruptive statistical methods, computational intelligence, soft computing, and traditional symbolic AI.

Artificial intelligence is the combination of two amazing concepts namely science and engineering. With the infusion of disruptive trends and human intelligence, intelligent machines and intelligent computing programs are emerging. Slowly, the flare of innovations moved away from IT and entered into diverse industries including healthcare, education, finance, marketing, business, telecommunication, etc. Organizations realized that by digitizing repetitive tasks, an enterprise can cut the cost of paperwork and labor which further eliminates human error, thus boosting efficiency. Automating processes involve employing artificial intelligence solutions that can support digitization and deliver data-driven insights. Artificial intelligence startups emerge as a ready-made solution provider that supports every company’s individual needs. AI startups in 2021 use big data to sophisticated AI models and leverage new solutions that could better serve customers. Analytics Insight has listed the top 100 artificial intelligence startups that are driving the next-generation development in technology.

Eg :

1. 8topuz

Headquarter(s): Limassol, Cyprus

Founded: 2010

Focus Area: AI Trading Software, Automated AI Software

Sector: Fintech

Website: https://8topuz.com/

8topuz is a disruptive fintech company that offers an easy-to-access AI-based automated investment system to effectively help customers grow their wealth regardless of their knowledge in trading. 8topuz’s application is designed to work both for investors and non-investors who want to increase their wealth with a fully automated AI-based trading system that is easy to set up and requires no management. It democratizes the way investments are done by bringing sophisticated elite trading technology to laymen. 8topuz’s uses the blend of artificial intelligence and machine learning to leverage next-generation trading software that follows risk management principles.

 

2. Accrad

Headquarter(s): 2020

Founded: Cape Town, South Africa

Focus Area: Artificial Intelligence, Deep Learning, Medical AI Software

Sector: Healthcare

Website: http://accrad.com/

Accrad is a health tech company that assists radiologists to reduce their workload with the precision of artificial intelligence. Radiologists work under different circumstances and deadlines and might find diagnosis through x-rays a bit difficult. Therefore, Accrad has come up with a futuristic solution to help with accurate and fast image diagnosis. The company has made x-ray processing more convincing and simpler. Its signature product CheXRad, a deep learning algorithm that identifies locations in the chest radiograph has the capability to predict 15 different diseases including Covid-19.

 

3. Affable.ai 

Headquarter(s): Suntec Tower One, Singapore

Founded: 2017

Focus Area: Influencer Marketing, Data-driven Marketing Solution, Big Data

Sector: Marketing

Website: https://www.affable.ai/

Affable.ai is a data-driven influencer marketing platform where customers can find relevant and authentic influencers and manage marketing operations. By using cutting-edge computer vision algorithms on social media posts, the company delivers actionable insights about micro-influencers and their audience. Similar to how Google has sophisticated its search and promote relative ads to users, Affable.ai has also built one-click marketing at a shorter scale. Recently, the company has raised US$2 million from Prime Venture Partners, Decacorn Capital, and SGInnovate. Affable.ai was planning to use the funding to expand its international presence into markets such as the US.

 

4. Affirm

Headquarter(s): San Francisco, California

Founded: 2012

Focus Area: Artificial Intelligence, Machine Learning, Data Science

Sector: Fintech

Website: https://www.affirm.com/

If you are thinking of buying a new product or shop for a necessary dress, or go on a trip, but has funding issues, then affirm can help you with installment loans. Affirm is a futuristic fintech company that offers loans to customers at the point of sale. The company aims to revolutionize the banking industry to be more accountable and accessible to consumers. Affirm has partnered with over 2,000 merchants including familiar brands across travel, personal fitness, electronics, apparel and beauty, and more to give shoppers a wide range of options. When the customers check out, they can get a load facility from the company. Affirm has closed a US$500 million securitization of its point-of-sale (POS) installment lands, which will help boost its growth in the future.

 

5. AI. Reverie

Headquarter(s): New York

Founded: 2017

Focus Area: Artificial Intelligence, Big Data, Machine Learning

Sector: Diverse Industries

Website: https://aireverie.com/

Reverie is one of the few companies that are working with synthetic data to leverage privacy-preserving data applications. It is an innovative platform that leverages data to train machine learning algorithms, which could eventually enhance machines’ understanding of the world. The company offers a suite of synthetic data and vision APIs to help businesses across different industries improve their AI applications. As an overall move, the solutions help in the creation of smart cities, sustainable farms, safer homes, etc. AI. Reverie has recently appointed Aayush Prakash, a former Nvidia Deep Learning expert as the Head of its Machine Learning team.

 

6. Aidoc

Headquarter(s): Tel Aviv, Israel

Founded: 2016

Focus Area: Image Analysis, Artificial Intelligence

Sector: Healthcare

Website: https://www.aidoc.com/

Aidoc is a health tech company that innovates to serve physicians’ needs and to create a measured impact on the imaging workflow. Founded in 2016, the company supports and enhances the impact of radiologist diagnostic power by helping physicians expedite patient treatment and improve the quality of care. To leverage the perfect solution, Aidoc’s leadership team has worked together on operation AI with the unprecedented healthcare market in mind. A month ago, Aidoc has raised US$65 million in Series C funding, which will help the company enhance its medical imaging platform.

 

7. Aira

Headquarter(s): California, United States

Founded: 2015

Focus Area: Wearable, Software, Assistive Technology

Sector: Computer Software

Website: https://aira.io/

Aira provides tech-enabled services for over 300 million visually impaired people around the globe. The company is aiming to deliver instant access to visual information from anyone, anytime, and anywhere. Aira’s assistive services blend wearable technology, artificial intelligence, and augmented reality to empower a network of trained, professional agents to remotely assist people who are blind or have low vision. Aira has raised US$12 million in a funding round led by private investors including Jawad Ahsan, Lori Greiner, and Robert Herjavec. The company said that it would use the funding to accelerate its capacity for innovation.

 

8. Airobotics

Headquarter(s): Tel Aviv, Israel

Founded: 2014

Focus Area: Automated Drones

Sector: Mining, Seaports, Oil & Gas, Industrial Facilities

Website: https://www.airoboticsdrones.com

Airobotics is an automated drone platform that develops pilotless drone solutions and offers an end-to-end, fully automated platform for collecting aerial data and gaining valuable insights. The industry-grade platform is available on-site and on-demand, enabling industrial facilities to access premium aerial data in a faster, safer, and more efficient way. With a merger of aerospace hardware design, robust electronic systems, and leading software engineers, Airobotics is leveraging sophisticated commercial drone operations.

 

9. Aisera

Headquarter(s): Palo Alto, California, United States

Founded: 2017

Focus Area: AI Service Desk, AI Customer Service, Conversational AI, Conversational RPA, AIOps

Sector: Call Centers, Customer Service, HR, IT, Sales & Marketing

Website: https://aisera.com/

Aisera is an AI services company providing an AI-driven solution to change the daily routines of employees and customers. Aisera aims to help users with greater self-service by automating common to complex actions, tasks, ad workflow. This enables users to focus on high-value work, while those requesting help can resolve their issues with self-service resolutions. The company recently announced that it would be partnering with Microsoft to deliver next-generation AI service desk solutions to automate requests. Besides, Aisera has also secured US$40 million in a recent Series C funding.

 

10. Alation

Headquarter(s): Redwood City, California, United States

Founded: 2012

Focus Area: Data Governance, Analytics, Cloud Transformation, Digital Transformation, DataOps, Business Analytics, Data Science

Sector: Finance, Healthcare, Insurance, Manufacturing, Retail, Technology, Public

Website: https://www.alation.com/

Alation is pioneering in providing a machine learning data catalog that helps people find, understand, and trust data across a certain organization. The company is leading the evolution into a platform for a broad range of data intelligence solutions including data search and discovery, data governance, data stewardship, analytics, and digital transformation. Alation goes a step beyond in delivering self-service analytics that allows everyone to explore and find insights into their data. The company has recently raised US$110 million in a Series D round led by Riverwood Capital with participation from new investors like Sanabil Investments and Snowflake Ventures.

Rest of list : 

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Top 10 books can provide information to the data storage architects who have an interest in Data Storage.

 

Data storage architects are entrusted with a great deal of responsibility. It is important to be able to manage huge volumes of data without issue. Books are a fantastic source for experts wanting to learn about a certain sector of technology, whether hardback or digital, and data storage architects are no exception. Here is a list of the top ten books for data storage architects. These books are prepared by writers with expertise and renown in data storage and are designed for both beginners and specialists.

1. The Artificial Intelligence Infrastructure Workshop

2. MongoDB: The Definitive Guide

3. Principles of Database Management

4. Software-Defined Data Infrastructure Essentials

5. The Data Warehouse Toolkit

6. Data Center Storage

7. The Enterprise Big Data Lake

8. The History of Data Storage

9. Information Storage and Management

10. Computer Engineering, Data Storage, Networking and Security

details : 

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TOP 10 MACHINE LEARNING ALGORITHMS FOR BEGINNERS

 It’s never too late to start off with machine learning basics

There’s no denying that the area of machine learning or artificial intelligence has grown in prominence in recent years. Machine learning is very effective for making predictions or calculating suggestions based on vast quantities of data, which is the trendiest topic in the tech sector right now. In this article, we will discuss the top 10 ML algorithms for newbies.

What are machine learning algorithms?

Any other algorithm in computer programming can be connected to a machine learning method. An ML algorithm is a data-driven process for developing a production-ready ML model. If you consider ML as a train that will get you to your destination, then ML algorithms are the engines that will get you there. The sort of ML algorithm that works best is determined by the business challenge at hand, the dataset’s structure, and the available resources.

Types of Machine Learning Algorithms

• Supervised ML Algorithms
• Unsupervised ML Algorithms
• Reinforcement ML Algorithms

Best ML Algorithms

1. Decision Tree

The decision tree is a decision-making aid that employs a tree-like graph or model of options, as well as their potential consequences, such as chance-event results, resource costs, and execution.

2. Principal Component Analysis

When data contains several dimensions, dimension reduction methods are among the most essential algorithms in ML.

3. Deep Learning Algorithms.

Deep learning algorithms are based on the neurological system of a person and are usually built on neural networks that have a lot of computing power. To execute certain tasks, all of these algorithms employ various forms of neural networks.

4. Naive Bayes Classifier

There are two sorts of probability in the model:

• Probability of each class
• Conditional Probability

5. Ordinary Least Square Regression

The least-square is the technique for doing linear regression in statistics. The traditional least-squares approach is to draw a clear line between an independent variable and a dependent variable, then compute the vertical distance between the spot and the line for each data set, and add them up.

 

6. Linear Regression

Linear regression describes the effect on the dependent variable when the independent variable is changed; as a result, the independent variable is referred to as the explained variable, and the dependent variable is referred to as the factor of interest.

7. Logistic Regression

A useful statistical method for modeling a binomial output including one or more explanatory factors is logistic regression. It calculates the relationship between the categorical dependent variable and one or even more independent variables by using a logistic function to measure probabilities.

8. Support Vector Machines

In SVM, a hyperplane is used to correctly divide the data points throughout the input variable space by their corresponding class, which is either 0 or 1.

9. Clustering Algorithms

Clustering is a data analysis method of finding meaningful data patterns, such as groupings of consumers based on their behavior or geography, because it is an unsupervised learning issue.

10. Gradient Boosting & AdaBoost

When dealing with large amounts of data, boosting algorithms are employed to make very accurate predictions. It is an ensemble learning method that mixes the different susceptible and mediocre predictors to produce strong predictors or estimators by combining the predictive power of varied base estimators in order to improve resilience.

Conclusion

Machine learning algorithms assist automate manual processes to make our lives easier, from simple day-to-day operations to making systems smarter. Machine learning’s importance has increased even more, which is why eager data scientists and engineers are eager to acquire new approaches to improve their abilities.

 original resources : 

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TOP 5 PYTHON IDES AND CODE EDITORS IN 2021

 Python is mostly used for server-side web development, software development, arithmetic, scripting, and artificial intelligence (AI). IDEs stands for Integrated Development Environments. It is a software package that includes tools for developing and testing software. The IDE aids in the automation of a developer’s activity by minimizing manual efforts and bringing all of the tools together in a single framework. A code editor is essentially a text editor in which a programmer may create code for the development of any software. The developer can also save tiny text files for the code in the code editor. Code editors, in comparison to IDEs, are quick to use and have a small size.

 

PyCharm:

Jet Brains produced PyCharm, which is one of the most frequently used Python IDEs. It is one of the top Python IDEs. PyCharm is all a Python developer needs to get things done. PyCharm allows developers to build clean, maintainable code. It aids productivity and provides smart support to developers. It includes a smart code editor, smart code navigation, and quick and safe refactoring.

 

Spyder:

Spyder is another well-known IDE brand. It’s an excellent Python compiler. It is well-known for python programming. It was created primarily for scientists and engineers to provide Python a robust scientific environment. It has advanced editing, debugging, and data exploring capabilities. It has a nice plugin system and API and is extremely expandable. A developer can use Spyder as an extension because it utilizes PYQT. It’s a capable IDE. It is one of the top Python IDEs.

 

Pydev:

It is also one of the top Python IDEs. PyDev is a third-party Eclipse plugin. It’s a Python programming environment in the form of an IDE. It has a linear size. It mainly focuses on the refactoring of python code, debugging in the graphical style, analysis of code, etc. Python interpreter with a lot of power.

 

Idle:

Idle is a well-known Python-based integrated development environment that has been integrated with the default language. It is one of the top Python IDEs. Idle is a very basic and simple IDE that is mostly used by beginning-level developers that wish to experiment with Python. It’s also cross-platform, which helps new developers a lot, but it’s also known as a disposable IDE since after learning the basics, a developer goes on to a more advanced IDE.

 

Wing:

The wing is another popular and capable IDE on the market today, with several useful features for python development. It has a powerful debugger and a smart editor that make interactive Python development quick, accurate, and enjoyable. Wing also offers a 30-day trial edition for developers to get a feel for the software’s capabilities.

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TOP 10 DATA SCIENCE JOBS TO APPLY IN SEPTEMBER 2021

 

Looking for a job in the field of data science? Check out these new openings

Presently, the data science course is one of the top courses that assist you to land trending job areas globally. If you are pursuing a data science course or you are already a data scientist then, without a doubt, it is the best profession to pursue your career in the present developing world.

Each organization has its necessities with regards to data science; nonetheless, various jobs are directly or indirectly, related to data science, these jobs are data scientists, data engineers, data architects, machine learning engineers, big data engineers, and artificial intelligence experts.

Here are the top 10 data science jobs to apply for in September 2021:

 1. Senior Manager – Data Science at Bain & Company

Location: Bangalore

2. Senior Manager – Data Science at The Smart Cube

Location: Noida/Gurgaon

3. Data Scientist – Banking/Insurance at Aureus Analytics

Location: Mumbai

4. Data Scientist – Product Owner at Dell

Location: Bangalore

5. Data Scientist – Advanced Machine Learning at Thoucentric

Location: Bangalore

6. Data Scientist – Advanced Analytics at Eclerx

Location: Pune

7. Data Scientist at Analytos

Location: Kolkata

8. Data Scientist at Jumio Corporation

Location: Jaipur, Rajasthan

9. Data Scientist – C3 Developer at Shell

Location: Chennai/Bangalore

10. Data Scientist at IBM

Location: Bangalore

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