![\"Job](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/Job-positions-for-machine-learning-professionals-300x200.jpg\")
<\/p>\n
While<\/em> the demand for machine learning professionals<\/strong><\/em><\/a> is likely to increase in the near future, an array of industries have already paved the path with lucrative pay packets and the offer of a rewarding career.<\/span> We\u2019re going to shed some light on the most in-demand machine learning jobs<\/strong> available in the field right now.<\/p>\n
1.1- Machine learning engineer<\/em><\/strong><\/h4>\n![\"\"](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/Machine-learning-engineer-300x200.jpeg\")
<\/p>\n
It\u2019s<\/em> usually considered as the initial role among all machine learning jobs<\/strong>. Machine learning engineers<\/strong><\/em><\/a> create algorithms to help decipher meaningful patterns from massive amounts of data.<\/span> These people also develop applications, which can perform common tasks done by humans in order to generate effective results without errors.<\/p>\n
1.2- Data scientist<\/em><\/strong><\/h4>\n![\"Data](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/Data-scientist-300x200.jpeg\")
<\/p>\n
Being<\/em> one of the most in-demand machine learning jobs<\/strong>, data scientists<\/strong> <\/em><\/a>are primarily involved in gathering data from different touchpoints, analyzing and interpreting it, drawing insights and inferences, and coming up with forward-looking solutions for business concerns. <\/span><\/p>\n
1.3- Data analyst<\/em><\/strong><\/h4>\n![\"Data](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/Data-analyst-300x194.jpg\")
<\/p>\n
These<\/em> people are expected to be familiar with data retrieval, data visualization, data warehousing<\/em>, Hadoop-based analysis, and other business intelligence concepts.<\/p>\n
A strong background in statistics, mathematics, machine learning, and programming is required to excel in this position.<\/span> Core responsibilities of these persistent data miners include designing and deploying algorithms, triaging code issues, culling information and identifying risk, and data pruning, among others.<\/p>\n
1.4- Business intelligence developer<\/em><\/strong><\/h4>\n![\"Business](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/Business-intelligence-developer-300x200.jpg\")
<\/p>\n
Apart<\/em> from applying skills on AI and machine learning<\/strong><\/em><\/a>, a business intelligence developer also holds strong business acumen.<\/p>\n
1.5- Research scientist<\/em><\/strong><\/h4>\n![\"Research](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/Research-scientist-300x200.jpg\")
<\/p>\n
This<\/em> interdisciplinary role requires the person to go back and forth while working between projects related to machine learning and artificial intelligence. He\/she should be involved in natural language processing<\/strong><\/em><\/a>, deep learning<\/strong><\/em><\/a>, reinforcement learning, and computer perception, among others. Some of the key skills required to become a research scientist include distributed computing, parallel computing, as well as computer architecture and algorithms.<\/span><\/p>\n
2- Much sought-after companies for machine learning jobs<\/em><\/strong><\/h3>\n![\"Much](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/Much-sought-after-companies-for-machine-learning-jobs-300x200.jpg\")
<\/p>\n
Today<\/em>, more and more organizations are integrating machine learning<\/strong> along with AI<\/strong> in their products, and in the coming years, this trend is only going to increase.<\/span><\/p>\n
Companies of different sizes and from different fields are expanding their capability, intelligence, and speed of human potential through their software. And this makes it the time to grab one of the varied machine learning jobs<\/strong>. Here, we\u2019ve consolidated a list of some highly-acclaimed machine learning companies that you can focus upon to get hired.<\/p>\n
2.1- Amazon<\/em><\/strong><\/h4>\n![\"amazon\"](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/amazon.png\")
<\/p>\n
From<\/em> Kindle to Echo to online store \u2013 machine learning is implemented on all Amazon<\/strong> <\/em><\/a>consumer services.<\/span> At Amazon, there\u2019re lots of teams that depend on machine learning \u2013 from Amazon JHIM, Amazon Music, to Alexa Engine, to Customer Service Personalization etc. With machine learning at its heart, Amazon is certainly one of the best companies that offer a diverse range of machine learning jobs<\/strong> to enthusiasts.<\/p>\n
2.2- Google<\/em><\/strong><\/h4>\n![\"google](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/google-300x200.jpeg\")
<\/p>\n
Unquestionably<\/em>, Google<\/strong><\/em><\/a> is one of the most powerful forces when it comes to implementing machine learning. Over the past few years, the giant has centered its focus on machine learning to enhance Google Language, Visual Processing, Speech Recognition, Search Engine Ranking, Image Processing<\/strong> <\/em><\/a>etc.<\/p>\n
2.3- Uber<\/em><\/strong><\/h4>\n![\"uber](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/uber-300x200.jpg\")
<\/p>\n
If<\/em> you think of Uber<\/strong><\/em><\/a> as a ride-hailing business, you\u2019re wrong.<\/span> Its internal teams use a machine learning-as-a-service platform to seamlessly develop, deploy, and operate machine learning solutions at the company\u2019s scale.<\/p>\n
2.4- Facebook<\/em><\/strong><\/h4>\n![\"facebook](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/facebook-300x199.png\")
<\/p>\n
Machine learning<\/em> is used each and every day by users of Facebook<\/a><\/strong><\/em> without them realizing it.<\/span> Things like personalized news feed, friend tagging suggestions, friend suggestions, group recommendations, mutual friend analysis etc are done through implementation of machine learning.<\/p>\n
2.5- Apple<\/em><\/strong><\/h4>\n![\"apple](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/apple-300x200.jpeg\")
<\/p>\n
Siri<\/em> has been greatly enhanced by Apple<\/strong> <\/em><\/a>with the help of machine learning so that it can become more capable than just calling people in your contact list. Now, it can identify someone who emailed you recently but isn\u2019t in your contact list, for instance.<\/p>\n
2.6- Feedzai<\/em><\/strong><\/h4>\n![\"feedzai](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/feedzai.jpg\")
<\/p>\n
Founded<\/em> by university professors, Feedzai<\/strong><\/em><\/span><\/a> follows the goal of offering customers a safer and better experience, and providing end-to-end fraud prevention by implementing AI and machine learning. It offers support to brick-and-mortar, as well as online stores, and helps them in acquiring knowledge for every sale. Based on behavioral analysis, it enables analysts to prevent and predict electronic payment loss in real time.<\/p>\n
2.7- Darktrace<\/em><\/strong><\/h4>\n![\"Darktrace](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/Darktrace.png\")
<\/p>\n
AI<\/em> and machine learning<\/strong> are used by Darktrace<\/strong><\/em><\/a> to offer cyber defense systems that impersonate the human immune system by understanding what is normal for all users and devices, modifying its understanding with environmental changes, and finding abnormalities that could uncover security issues.<\/p>\n
2.8- IBM Watson<\/em><\/strong><\/h4>\n![\"IBM](\"https:\/\/academy.magnimindacademy.com\/wp-content\/uploads\/2019\/03\/IBM-Watson-300x120.png\")
<\/p>\n
Apart<\/em> from transforming data, data scientists here apply machine learning algorithms<\/strong><\/em><\/a> for training predictive models and developing intelligent applications that leverage the predictions exhibited by machine learning models. Algorithms are also applied to learn from datasets to develop models that can generate predictions based on those datasets.<\/p>\n
If working for a trusted name in machine learning<\/strong> domain is something you look forward to, applying for a job at IBM Watson<\/strong><\/em><\/a> would be a good decision.<\/p>\n
Conclusion<\/em><\/strong><\/h3>\nThings<\/em> like increasing varieties and volumes of available data, cheaper and more powerful computational processing, and affordable data storage \u2013 all have heavily influenced the rapid growth of machine learning. Today, it has become possible to automatically and quickly produce models that are capable of analyzing bigger and more complex datasets, and can deliver more accurate results faster – even on an extremely large scale.<\/span> And with the help of precise models, companies stand a better chance of finding profitable opportunities out as well as avoiding unknown risks.<\/p>\n
There\u2019s no wonder why machine learning is being adopted by businesses across the globe. By gleaning insights from available data, often in real time, businesses are also gaining a huge advantage over their competitors.<\/span> Because of all these, we\u2019re experiencing a huge influx of machine learning jobs<\/strong> that are to be filled. This presents a great opportunity for machine learning enthusiasts that they should leverage.<\/p>\n
<\/p>\n<\/p>\n
Being<\/em> one of the most in-demand machine learning jobs<\/strong>, data scientists<\/strong> <\/em><\/a>are primarily involved in gathering data from different touchpoints, analyzing and interpreting it, drawing insights and inferences, and coming up with forward-looking solutions for business concerns. <\/span><\/p>\n
1.3- Data analyst<\/em><\/strong><\/h4>\n<\/p>\n
These<\/em> people are expected to be familiar with data retrieval, data visualization, data warehousing<\/em>, Hadoop-based analysis, and other business intelligence concepts.<\/p>\n
A strong background in statistics, mathematics, machine learning, and programming is required to excel in this position.<\/span> Core responsibilities of these persistent data miners include designing and deploying algorithms, triaging code issues, culling information and identifying risk, and data pruning, among others.<\/p>\n
1.4- Business intelligence developer<\/em><\/strong><\/h4>\n<\/p>\n
Apart<\/em> from applying skills on AI and machine learning<\/strong><\/em><\/a>, a business intelligence developer also holds strong business acumen.<\/p>\n
1.5- Research scientist<\/em><\/strong><\/h4>\n<\/p>\n
This<\/em> interdisciplinary role requires the person to go back and forth while working between projects related to machine learning and artificial intelligence. He\/she should be involved in natural language processing<\/strong><\/em><\/a>, deep learning<\/strong><\/em><\/a>, reinforcement learning, and computer perception, among others. Some of the key skills required to become a research scientist include distributed computing, parallel computing, as well as computer architecture and algorithms.<\/span><\/p>\n
2- Much sought-after companies for machine learning jobs<\/em><\/strong><\/h3>\n<\/p>\n
Today<\/em>, more and more organizations are integrating machine learning<\/strong> along with AI<\/strong> in their products, and in the coming years, this trend is only going to increase.<\/span><\/p>\n
Companies of different sizes and from different fields are expanding their capability, intelligence, and speed of human potential through their software. And this makes it the time to grab one of the varied machine learning jobs<\/strong>. Here, we\u2019ve consolidated a list of some highly-acclaimed machine learning companies that you can focus upon to get hired.<\/p>\n
2.1- Amazon<\/em><\/strong><\/h4>\n<\/p>\n
From<\/em> Kindle to Echo to online store \u2013 machine learning is implemented on all Amazon<\/strong> <\/em><\/a>consumer services.<\/span> At Amazon, there\u2019re lots of teams that depend on machine learning \u2013 from Amazon JHIM, Amazon Music, to Alexa Engine, to Customer Service Personalization etc. With machine learning at its heart, Amazon is certainly one of the best companies that offer a diverse range of machine learning jobs<\/strong> to enthusiasts.<\/p>\n
2.2- Google<\/em><\/strong><\/h4>\n<\/p>\n
Unquestionably<\/em>, Google<\/strong><\/em><\/a> is one of the most powerful forces when it comes to implementing machine learning. Over the past few years, the giant has centered its focus on machine learning to enhance Google Language, Visual Processing, Speech Recognition, Search Engine Ranking, Image Processing<\/strong> <\/em><\/a>etc.<\/p>\n
2.3- Uber<\/em><\/strong><\/h4>\n<\/p>\n
If<\/em> you think of Uber<\/strong><\/em><\/a> as a ride-hailing business, you\u2019re wrong.<\/span> Its internal teams use a machine learning-as-a-service platform to seamlessly develop, deploy, and operate machine learning solutions at the company\u2019s scale.<\/p>\n
2.4- Facebook<\/em><\/strong><\/h4>\n<\/p>\n
Machine learning<\/em> is used each and every day by users of Facebook<\/a><\/strong><\/em> without them realizing it.<\/span> Things like personalized news feed, friend tagging suggestions, friend suggestions, group recommendations, mutual friend analysis etc are done through implementation of machine learning.<\/p>\n
2.5- Apple<\/em><\/strong><\/h4>\n<\/p>\n
Siri<\/em> has been greatly enhanced by Apple<\/strong> <\/em><\/a>with the help of machine learning so that it can become more capable than just calling people in your contact list. Now, it can identify someone who emailed you recently but isn\u2019t in your contact list, for instance.<\/p>\n
2.6- Feedzai<\/em><\/strong><\/h4>\n<\/p>\n
Founded<\/em> by university professors, Feedzai<\/strong><\/em><\/span><\/a> follows the goal of offering customers a safer and better experience, and providing end-to-end fraud prevention by implementing AI and machine learning. It offers support to brick-and-mortar, as well as online stores, and helps them in acquiring knowledge for every sale. Based on behavioral analysis, it enables analysts to prevent and predict electronic payment loss in real time.<\/p>\n
2.7- Darktrace<\/em><\/strong><\/h4>\n<\/p>\n
AI<\/em> and machine learning<\/strong> are used by Darktrace<\/strong><\/em><\/a> to offer cyber defense systems that impersonate the human immune system by understanding what is normal for all users and devices, modifying its understanding with environmental changes, and finding abnormalities that could uncover security issues.<\/p>\n
2.8- IBM Watson<\/em><\/strong><\/h4>\n<\/p>\n
Apart<\/em> from transforming data, data scientists here apply machine learning algorithms<\/strong><\/em><\/a> for training predictive models and developing intelligent applications that leverage the predictions exhibited by machine learning models. Algorithms are also applied to learn from datasets to develop models that can generate predictions based on those datasets.<\/p>\n
If working for a trusted name in machine learning<\/strong> domain is something you look forward to, applying for a job at IBM Watson<\/strong><\/em><\/a> would be a good decision.<\/p>\n
Conclusion<\/em><\/strong><\/h3>\nThings<\/em> like increasing varieties and volumes of available data, cheaper and more powerful computational processing, and affordable data storage \u2013 all have heavily influenced the rapid growth of machine learning. Today, it has become possible to automatically and quickly produce models that are capable of analyzing bigger and more complex datasets, and can deliver more accurate results faster – even on an extremely large scale.<\/span> And with the help of precise models, companies stand a better chance of finding profitable opportunities out as well as avoiding unknown risks.<\/p>\n
There\u2019s no wonder why machine learning is being adopted by businesses across the globe. By gleaning insights from available data, often in real time, businesses are also gaining a huge advantage over their competitors.<\/span> Because of all these, we\u2019re experiencing a huge influx of machine learning jobs<\/strong> that are to be filled. This presents a great opportunity for machine learning enthusiasts that they should leverage.<\/p>\n
<\/p>\n<\/p>\n
Apart<\/em> from applying skills on AI and machine learning<\/strong><\/em><\/a>, a business intelligence developer also holds strong business acumen.<\/p>\n
1.5- Research scientist<\/em><\/strong><\/h4>\n<\/p>\n
This<\/em> interdisciplinary role requires the person to go back and forth while working between projects related to machine learning and artificial intelligence. He\/she should be involved in natural language processing<\/strong><\/em><\/a>, deep learning<\/strong><\/em><\/a>, reinforcement learning, and computer perception, among others. Some of the key skills required to become a research scientist include distributed computing, parallel computing, as well as computer architecture and algorithms.<\/span><\/p>\n
2- Much sought-after companies for machine learning jobs<\/em><\/strong><\/h3>\n<\/p>\n
Today<\/em>, more and more organizations are integrating machine learning<\/strong> along with AI<\/strong> in their products, and in the coming years, this trend is only going to increase.<\/span><\/p>\n
Companies of different sizes and from different fields are expanding their capability, intelligence, and speed of human potential through their software. And this makes it the time to grab one of the varied machine learning jobs<\/strong>. Here, we\u2019ve consolidated a list of some highly-acclaimed machine learning companies that you can focus upon to get hired.<\/p>\n
2.1- Amazon<\/em><\/strong><\/h4>\n<\/p>\n
From<\/em> Kindle to Echo to online store \u2013 machine learning is implemented on all Amazon<\/strong> <\/em><\/a>consumer services.<\/span> At Amazon, there\u2019re lots of teams that depend on machine learning \u2013 from Amazon JHIM, Amazon Music, to Alexa Engine, to Customer Service Personalization etc. With machine learning at its heart, Amazon is certainly one of the best companies that offer a diverse range of machine learning jobs<\/strong> to enthusiasts.<\/p>\n
2.2- Google<\/em><\/strong><\/h4>\n<\/p>\n
Unquestionably<\/em>, Google<\/strong><\/em><\/a> is one of the most powerful forces when it comes to implementing machine learning. Over the past few years, the giant has centered its focus on machine learning to enhance Google Language, Visual Processing, Speech Recognition, Search Engine Ranking, Image Processing<\/strong> <\/em><\/a>etc.<\/p>\n
2.3- Uber<\/em><\/strong><\/h4>\n<\/p>\n
If<\/em> you think of Uber<\/strong><\/em><\/a> as a ride-hailing business, you\u2019re wrong.<\/span> Its internal teams use a machine learning-as-a-service platform to seamlessly develop, deploy, and operate machine learning solutions at the company\u2019s scale.<\/p>\n
2.4- Facebook<\/em><\/strong><\/h4>\n<\/p>\n
Machine learning<\/em> is used each and every day by users of Facebook<\/a><\/strong><\/em> without them realizing it.<\/span> Things like personalized news feed, friend tagging suggestions, friend suggestions, group recommendations, mutual friend analysis etc are done through implementation of machine learning.<\/p>\n
2.5- Apple<\/em><\/strong><\/h4>\n<\/p>\n
Siri<\/em> has been greatly enhanced by Apple<\/strong> <\/em><\/a>with the help of machine learning so that it can become more capable than just calling people in your contact list. Now, it can identify someone who emailed you recently but isn\u2019t in your contact list, for instance.<\/p>\n
2.6- Feedzai<\/em><\/strong><\/h4>\n<\/p>\n
Founded<\/em> by university professors, Feedzai<\/strong><\/em><\/span><\/a> follows the goal of offering customers a safer and better experience, and providing end-to-end fraud prevention by implementing AI and machine learning. It offers support to brick-and-mortar, as well as online stores, and helps them in acquiring knowledge for every sale. Based on behavioral analysis, it enables analysts to prevent and predict electronic payment loss in real time.<\/p>\n
2.7- Darktrace<\/em><\/strong><\/h4>\n<\/p>\n
AI<\/em> and machine learning<\/strong> are used by Darktrace<\/strong><\/em><\/a> to offer cyber defense systems that impersonate the human immune system by understanding what is normal for all users and devices, modifying its understanding with environmental changes, and finding abnormalities that could uncover security issues.<\/p>\n
2.8- IBM Watson<\/em><\/strong><\/h4>\n<\/p>\n
Apart<\/em> from transforming data, data scientists here apply machine learning algorithms<\/strong><\/em><\/a> for training predictive models and developing intelligent applications that leverage the predictions exhibited by machine learning models. Algorithms are also applied to learn from datasets to develop models that can generate predictions based on those datasets.<\/p>\n
If working for a trusted name in machine learning<\/strong> domain is something you look forward to, applying for a job at IBM Watson<\/strong><\/em><\/a> would be a good decision.<\/p>\n
Conclusion<\/em><\/strong><\/h3>\nThings<\/em> like increasing varieties and volumes of available data, cheaper and more powerful computational processing, and affordable data storage \u2013 all have heavily influenced the rapid growth of machine learning. Today, it has become possible to automatically and quickly produce models that are capable of analyzing bigger and more complex datasets, and can deliver more accurate results faster – even on an extremely large scale.<\/span> And with the help of precise models, companies stand a better chance of finding profitable opportunities out as well as avoiding unknown risks.<\/p>\n
There\u2019s no wonder why machine learning is being adopted by businesses across the globe. By gleaning insights from available data, often in real time, businesses are also gaining a huge advantage over their competitors.<\/span> Because of all these, we\u2019re experiencing a huge influx of machine learning jobs<\/strong> that are to be filled. This presents a great opportunity for machine learning enthusiasts that they should leverage.<\/p>\n
<\/p>\n<\/p>\n
Today<\/em>, more and more organizations are integrating machine learning<\/strong> along with AI<\/strong> in their products, and in the coming years, this trend is only going to increase.<\/span><\/p>\n
Companies of different sizes and from different fields are expanding their capability, intelligence, and speed of human potential through their software. And this makes it the time to grab one of the varied machine learning jobs<\/strong>. Here, we\u2019ve consolidated a list of some highly-acclaimed machine learning companies that you can focus upon to get hired.<\/p>\n
2.1- Amazon<\/em><\/strong><\/h4>\n<\/p>\n
From<\/em> Kindle to Echo to online store \u2013 machine learning is implemented on all Amazon<\/strong> <\/em><\/a>consumer services.<\/span> At Amazon, there\u2019re lots of teams that depend on machine learning \u2013 from Amazon JHIM, Amazon Music, to Alexa Engine, to Customer Service Personalization etc. With machine learning at its heart, Amazon is certainly one of the best companies that offer a diverse range of machine learning jobs<\/strong> to enthusiasts.<\/p>\n
2.2- Google<\/em><\/strong><\/h4>\n<\/p>\n
Unquestionably<\/em>, Google<\/strong><\/em><\/a> is one of the most powerful forces when it comes to implementing machine learning. Over the past few years, the giant has centered its focus on machine learning to enhance Google Language, Visual Processing, Speech Recognition, Search Engine Ranking, Image Processing<\/strong> <\/em><\/a>etc.<\/p>\n
2.3- Uber<\/em><\/strong><\/h4>\n<\/p>\n
If<\/em> you think of Uber<\/strong><\/em><\/a> as a ride-hailing business, you\u2019re wrong.<\/span> Its internal teams use a machine learning-as-a-service platform to seamlessly develop, deploy, and operate machine learning solutions at the company\u2019s scale.<\/p>\n
2.4- Facebook<\/em><\/strong><\/h4>\n<\/p>\n
Machine learning<\/em> is used each and every day by users of Facebook<\/a><\/strong><\/em> without them realizing it.<\/span> Things like personalized news feed, friend tagging suggestions, friend suggestions, group recommendations, mutual friend analysis etc are done through implementation of machine learning.<\/p>\n
2.5- Apple<\/em><\/strong><\/h4>\n<\/p>\n
Siri<\/em> has been greatly enhanced by Apple<\/strong> <\/em><\/a>with the help of machine learning so that it can become more capable than just calling people in your contact list. Now, it can identify someone who emailed you recently but isn\u2019t in your contact list, for instance.<\/p>\n
2.6- Feedzai<\/em><\/strong><\/h4>\n<\/p>\n
Founded<\/em> by university professors, Feedzai<\/strong><\/em><\/span><\/a> follows the goal of offering customers a safer and better experience, and providing end-to-end fraud prevention by implementing AI and machine learning. It offers support to brick-and-mortar, as well as online stores, and helps them in acquiring knowledge for every sale. Based on behavioral analysis, it enables analysts to prevent and predict electronic payment loss in real time.<\/p>\n
2.7- Darktrace<\/em><\/strong><\/h4>\n<\/p>\n
AI<\/em> and machine learning<\/strong> are used by Darktrace<\/strong><\/em><\/a> to offer cyber defense systems that impersonate the human immune system by understanding what is normal for all users and devices, modifying its understanding with environmental changes, and finding abnormalities that could uncover security issues.<\/p>\n
2.8- IBM Watson<\/em><\/strong><\/h4>\n<\/p>\n
Apart<\/em> from transforming data, data scientists here apply machine learning algorithms<\/strong><\/em><\/a> for training predictive models and developing intelligent applications that leverage the predictions exhibited by machine learning models. Algorithms are also applied to learn from datasets to develop models that can generate predictions based on those datasets.<\/p>\n
If working for a trusted name in machine learning<\/strong> domain is something you look forward to, applying for a job at IBM Watson<\/strong><\/em><\/a> would be a good decision.<\/p>\n
Conclusion<\/em><\/strong><\/h3>\nThings<\/em> like increasing varieties and volumes of available data, cheaper and more powerful computational processing, and affordable data storage \u2013 all have heavily influenced the rapid growth of machine learning. Today, it has become possible to automatically and quickly produce models that are capable of analyzing bigger and more complex datasets, and can deliver more accurate results faster – even on an extremely large scale.<\/span> And with the help of precise models, companies stand a better chance of finding profitable opportunities out as well as avoiding unknown risks.<\/p>\n
There\u2019s no wonder why machine learning is being adopted by businesses across the globe. By gleaning insights from available data, often in real time, businesses are also gaining a huge advantage over their competitors.<\/span> Because of all these, we\u2019re experiencing a huge influx of machine learning jobs<\/strong> that are to be filled. This presents a great opportunity for machine learning enthusiasts that they should leverage.<\/p>\n
<\/p>\n<\/p>\n
Unquestionably<\/em>, Google<\/strong><\/em><\/a> is one of the most powerful forces when it comes to implementing machine learning. Over the past few years, the giant has centered its focus on machine learning to enhance Google Language, Visual Processing, Speech Recognition, Search Engine Ranking, Image Processing<\/strong> <\/em><\/a>etc.<\/p>\n
2.3- Uber<\/em><\/strong><\/h4>\n<\/p>\n
If<\/em> you think of Uber<\/strong><\/em><\/a> as a ride-hailing business, you\u2019re wrong.<\/span> Its internal teams use a machine learning-as-a-service platform to seamlessly develop, deploy, and operate machine learning solutions at the company\u2019s scale.<\/p>\n
2.4- Facebook<\/em><\/strong><\/h4>\n<\/p>\n
Machine learning<\/em> is used each and every day by users of Facebook<\/a><\/strong><\/em> without them realizing it.<\/span> Things like personalized news feed, friend tagging suggestions, friend suggestions, group recommendations, mutual friend analysis etc are done through implementation of machine learning.<\/p>\n
2.5- Apple<\/em><\/strong><\/h4>\n<\/p>\n
Siri<\/em> has been greatly enhanced by Apple<\/strong> <\/em><\/a>with the help of machine learning so that it can become more capable than just calling people in your contact list. Now, it can identify someone who emailed you recently but isn\u2019t in your contact list, for instance.<\/p>\n
2.6- Feedzai<\/em><\/strong><\/h4>\n<\/p>\n
Founded<\/em> by university professors, Feedzai<\/strong><\/em><\/span><\/a> follows the goal of offering customers a safer and better experience, and providing end-to-end fraud prevention by implementing AI and machine learning. It offers support to brick-and-mortar, as well as online stores, and helps them in acquiring knowledge for every sale. Based on behavioral analysis, it enables analysts to prevent and predict electronic payment loss in real time.<\/p>\n
2.7- Darktrace<\/em><\/strong><\/h4>\n<\/p>\n
AI<\/em> and machine learning<\/strong> are used by Darktrace<\/strong><\/em><\/a> to offer cyber defense systems that impersonate the human immune system by understanding what is normal for all users and devices, modifying its understanding with environmental changes, and finding abnormalities that could uncover security issues.<\/p>\n
2.8- IBM Watson<\/em><\/strong><\/h4>\n<\/p>\n
Apart<\/em> from transforming data, data scientists here apply machine learning algorithms<\/strong><\/em><\/a> for training predictive models and developing intelligent applications that leverage the predictions exhibited by machine learning models. Algorithms are also applied to learn from datasets to develop models that can generate predictions based on those datasets.<\/p>\n
If working for a trusted name in machine learning<\/strong> domain is something you look forward to, applying for a job at IBM Watson<\/strong><\/em><\/a> would be a good decision.<\/p>\n
Conclusion<\/em><\/strong><\/h3>\nThings<\/em> like increasing varieties and volumes of available data, cheaper and more powerful computational processing, and affordable data storage \u2013 all have heavily influenced the rapid growth of machine learning. Today, it has become possible to automatically and quickly produce models that are capable of analyzing bigger and more complex datasets, and can deliver more accurate results faster – even on an extremely large scale.<\/span> And with the help of precise models, companies stand a better chance of finding profitable opportunities out as well as avoiding unknown risks.<\/p>\n
There\u2019s no wonder why machine learning is being adopted by businesses across the globe. By gleaning insights from available data, often in real time, businesses are also gaining a huge advantage over their competitors.<\/span> Because of all these, we\u2019re experiencing a huge influx of machine learning jobs<\/strong> that are to be filled. This presents a great opportunity for machine learning enthusiasts that they should leverage.<\/p>\n
<\/p>\n<\/p>\n
Machine learning<\/em> is used each and every day by users of Facebook<\/a><\/strong><\/em> without them realizing it.<\/span> Things like personalized news feed, friend tagging suggestions, friend suggestions, group recommendations, mutual friend analysis etc are done through implementation of machine learning.<\/p>\n
2.5- Apple<\/em><\/strong><\/h4>\n<\/p>\n
Siri<\/em> has been greatly enhanced by Apple<\/strong> <\/em><\/a>with the help of machine learning so that it can become more capable than just calling people in your contact list. Now, it can identify someone who emailed you recently but isn\u2019t in your contact list, for instance.<\/p>\n
2.6- Feedzai<\/em><\/strong><\/h4>\n<\/p>\n
Founded<\/em> by university professors, Feedzai<\/strong><\/em><\/span><\/a> follows the goal of offering customers a safer and better experience, and providing end-to-end fraud prevention by implementing AI and machine learning. It offers support to brick-and-mortar, as well as online stores, and helps them in acquiring knowledge for every sale. Based on behavioral analysis, it enables analysts to prevent and predict electronic payment loss in real time.<\/p>\n
2.7- Darktrace<\/em><\/strong><\/h4>\n<\/p>\n
AI<\/em> and machine learning<\/strong> are used by Darktrace<\/strong><\/em><\/a> to offer cyber defense systems that impersonate the human immune system by understanding what is normal for all users and devices, modifying its understanding with environmental changes, and finding abnormalities that could uncover security issues.<\/p>\n
2.8- IBM Watson<\/em><\/strong><\/h4>\n<\/p>\n
Apart<\/em> from transforming data, data scientists here apply machine learning algorithms<\/strong><\/em><\/a> for training predictive models and developing intelligent applications that leverage the predictions exhibited by machine learning models. Algorithms are also applied to learn from datasets to develop models that can generate predictions based on those datasets.<\/p>\n
If working for a trusted name in machine learning<\/strong> domain is something you look forward to, applying for a job at IBM Watson<\/strong><\/em><\/a> would be a good decision.<\/p>\n
Conclusion<\/em><\/strong><\/h3>\nThings<\/em> like increasing varieties and volumes of available data, cheaper and more powerful computational processing, and affordable data storage \u2013 all have heavily influenced the rapid growth of machine learning. Today, it has become possible to automatically and quickly produce models that are capable of analyzing bigger and more complex datasets, and can deliver more accurate results faster – even on an extremely large scale.<\/span> And with the help of precise models, companies stand a better chance of finding profitable opportunities out as well as avoiding unknown risks.<\/p>\n
There\u2019s no wonder why machine learning is being adopted by businesses across the globe. By gleaning insights from available data, often in real time, businesses are also gaining a huge advantage over their competitors.<\/span> Because of all these, we\u2019re experiencing a huge influx of machine learning jobs<\/strong> that are to be filled. This presents a great opportunity for machine learning enthusiasts that they should leverage.<\/p>\n
<\/p>\n<\/p>\n
Founded<\/em> by university professors, Feedzai<\/strong><\/em><\/span><\/a> follows the goal of offering customers a safer and better experience, and providing end-to-end fraud prevention by implementing AI and machine learning. It offers support to brick-and-mortar, as well as online stores, and helps them in acquiring knowledge for every sale. Based on behavioral analysis, it enables analysts to prevent and predict electronic payment loss in real time.<\/p>\n
2.7- Darktrace<\/em><\/strong><\/h4>\n<\/p>\n
AI<\/em> and machine learning<\/strong> are used by Darktrace<\/strong><\/em><\/a> to offer cyber defense systems that impersonate the human immune system by understanding what is normal for all users and devices, modifying its understanding with environmental changes, and finding abnormalities that could uncover security issues.<\/p>\n
2.8- IBM Watson<\/em><\/strong><\/h4>\n<\/p>\n
Apart<\/em> from transforming data, data scientists here apply machine learning algorithms<\/strong><\/em><\/a> for training predictive models and developing intelligent applications that leverage the predictions exhibited by machine learning models. Algorithms are also applied to learn from datasets to develop models that can generate predictions based on those datasets.<\/p>\n
If working for a trusted name in machine learning<\/strong> domain is something you look forward to, applying for a job at IBM Watson<\/strong><\/em><\/a> would be a good decision.<\/p>\n
Conclusion<\/em><\/strong><\/h3>\nThings<\/em> like increasing varieties and volumes of available data, cheaper and more powerful computational processing, and affordable data storage \u2013 all have heavily influenced the rapid growth of machine learning. Today, it has become possible to automatically and quickly produce models that are capable of analyzing bigger and more complex datasets, and can deliver more accurate results faster – even on an extremely large scale.<\/span> And with the help of precise models, companies stand a better chance of finding profitable opportunities out as well as avoiding unknown risks.<\/p>\n
There\u2019s no wonder why machine learning is being adopted by businesses across the globe. By gleaning insights from available data, often in real time, businesses are also gaining a huge advantage over their competitors.<\/span> Because of all these, we\u2019re experiencing a huge influx of machine learning jobs<\/strong> that are to be filled. This presents a great opportunity for machine learning enthusiasts that they should leverage.<\/p>\n
<\/p>\n<\/p>\n
Apart<\/em> from transforming data, data scientists here apply machine learning algorithms<\/strong><\/em><\/a> for training predictive models and developing intelligent applications that leverage the predictions exhibited by machine learning models. Algorithms are also applied to learn from datasets to develop models that can generate predictions based on those datasets.<\/p>\n
If working for a trusted name in machine learning<\/strong> domain is something you look forward to, applying for a job at IBM Watson<\/strong><\/em><\/a> would be a good decision.<\/p>\n