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Text
ABOUT PELTARION
At Peltarion, the entire point of our work is to get our clients up to speed, to make it easy to start working with AI. We started working with AI and neural networks in 2004. At first, this came in the shape of two recent graduates of the Royal Technical Institute in Stockholm, Luka Crnkovic-Friis and Måns Erlandson.PELTARION PLATFORM
Peltarion is an AI platform based on deep learning where you can build, train, and deploy artificial intelligence models on your own. No Python or any code. PELTARION | BREAKING LANGUAGE BARRIERS WITH MULTILINGUAL NLP Breaking language barriers with multilingual NLP. Natural language processing (NLP) techniques aim to automatically process, analyze and manipulate language data like speech and text. The Peltarion platform enables a wide range of text solutions through our integrated language models (BERT, USE, XLM-R). Learn more about our language models. PELTARION | TURN SPEECH-TO-TEXT INTO ACTION The need for speech to text solutions are growing, and the use cases go far beyond transcription. Complaint analysis, call categorization, risk mitigation, and customer service are just a few examples of areas where businesses can benefit from speech to text solutions. 17 WAYS TO REACH THE UN'S SUSTAINABLE GOALS WITH AI Here’s what AI can do to help humanity reaching the UN’s 17 Sustainable Development Goals: SDG 01 / No poverty. With AI, we can learn to predict and prevent extreme climate-related events. To reduce vulnerability and exposure, also reducing poverty. BERT TEXT CLASSIFICATION NLP TUTORIAL Solve a text classification problem with BERT. In this tutorial, you will solve a text classification problem using BERT (Bidirectional Encoder Representations from Transformers). The input is an IMDB dataset consisting of movie reviews, tagged with either positive or negative sentiment – i.e., how a user or customer feels about themovie.
POISSON LOSS FUNCTION The poisson loss function is used for regression when modeling count data. Use for data follows the poisson distribution. Ex: churn of customers next week. The loss takes the form of: L ( y, y ^) = 1 N ∑ i = 0 N ( y ^ i − y i l o g y ^ i) L (y, \hat {y}) = \frac {1} {N} \sum_ {i=0}^ {N} ( {\hat {y}}_i - FEATURE DISTRIBUTION OF A FEATURE Feature distribution. Feature distribution. The distribution of a feature over its range, with value on the horizontal axis and frequency on the vertical axis. For string and categorical encoded integers, the feature distribution is displayed as a bar chart withthe highest, i.e.,
BERT - TEXT CLASSIFICATION / CHEAT SHEET - PELTARION Sentiment analysis (😃 or 😱 or 😡 or 😍 or ) Try yourself: HappyDB - happy moments is a corpus of more than 100,000 happy moments.. Ticket classification. Save time and enable a quicker response by classifying incoming customer service requests as a first step, e.g., by topic, or urgency. USING AI WEATHER PREDITIONS TO BALANCE ENERGY PRODUCTION Unlike gas, electricity can’t be stored in large quantities, and thus the ordered demand and supply must balance every day. With wind energy, both the demand and the supply – the wind itself – can be better predicted with stronger weather forecasting, thanks to AI.ABOUT PELTARION
At Peltarion, the entire point of our work is to get our clients up to speed, to make it easy to start working with AI. We started working with AI and neural networks in 2004. At first, this came in the shape of two recent graduates of the Royal Technical Institute in Stockholm, Luka Crnkovic-Friis and Måns Erlandson.PELTARION PLATFORM
Peltarion is an AI platform based on deep learning where you can build, train, and deploy artificial intelligence models on your own. No Python or any code. PELTARION | BREAKING LANGUAGE BARRIERS WITH MULTILINGUAL NLP Breaking language barriers with multilingual NLP. Natural language processing (NLP) techniques aim to automatically process, analyze and manipulate language data like speech and text. The Peltarion platform enables a wide range of text solutions through our integrated language models (BERT, USE, XLM-R). Learn more about our language models. PELTARION | TURN SPEECH-TO-TEXT INTO ACTION The need for speech to text solutions are growing, and the use cases go far beyond transcription. Complaint analysis, call categorization, risk mitigation, and customer service are just a few examples of areas where businesses can benefit from speech to text solutions. 17 WAYS TO REACH THE UN'S SUSTAINABLE GOALS WITH AI Here’s what AI can do to help humanity reaching the UN’s 17 Sustainable Development Goals: SDG 01 / No poverty. With AI, we can learn to predict and prevent extreme climate-related events. To reduce vulnerability and exposure, also reducing poverty. BERT TEXT CLASSIFICATION NLP TUTORIAL Solve a text classification problem with BERT. In this tutorial, you will solve a text classification problem using BERT (Bidirectional Encoder Representations from Transformers). The input is an IMDB dataset consisting of movie reviews, tagged with either positive or negative sentiment – i.e., how a user or customer feels about themovie.
POISSON LOSS FUNCTION The poisson loss function is used for regression when modeling count data. Use for data follows the poisson distribution. Ex: churn of customers next week. The loss takes the form of: L ( y, y ^) = 1 N ∑ i = 0 N ( y ^ i − y i l o g y ^ i) L (y, \hat {y}) = \frac {1} {N} \sum_ {i=0}^ {N} ( {\hat {y}}_i - FEATURE DISTRIBUTION OF A FEATURE Feature distribution. Feature distribution. The distribution of a feature over its range, with value on the horizontal axis and frequency on the vertical axis. For string and categorical encoded integers, the feature distribution is displayed as a bar chart withthe highest, i.e.,
BERT - TEXT CLASSIFICATION / CHEAT SHEET - PELTARION Sentiment analysis (😃 or 😱 or 😡 or 😍 or ) Try yourself: HappyDB - happy moments is a corpus of more than 100,000 happy moments.. Ticket classification. Save time and enable a quicker response by classifying incoming customer service requests as a first step, e.g., by topic, or urgency. USING AI WEATHER PREDITIONS TO BALANCE ENERGY PRODUCTION Unlike gas, electricity can’t be stored in large quantities, and thus the ordered demand and supply must balance every day. With wind energy, both the demand and the supply – the wind itself – can be better predicted with stronger weather forecasting, thanks to AI. AI AND DEEP LEARNING SOLUTIONS IN INSURANCE How AI and deep learning will improve customer-facing processes, risk assessment and backend efficiencies in the insurance industry PELTARION | TEXT CLASSIFICATION DATA AND PREPARATION The Peltarion Platform is an operational AI platform for building and deploying AI models that is capable of executing a broad range of deep learning-based use cases. PELTARION | IMAGE SEGMENTATION DATA AND PREPARATION The Peltarion Platform is an operational AI platform for building and deploying AI models that is capable of executing a broad range of deep learning-based use cases. PELTARION | TEXT CLASSIFICATION BEST PRACTICES In this tutorial, you will solve a text classification problem using BERT (Bidirectional Encoder Representations from Transformers). The input is an IMDB dataset consisting of movie reviews, tagged with either positive or negative sentiment – i.e., how a user or customer feels about the movie. PELTARION | IMAGE CLASSIFICATION BEST PRACTICES Save training time and create well-performing models with small datasets. Sounds good? This tutorial will teach you how. By using transfer learning with our pretrained snippets, you can create a well-performing model even though you have a small dataset. FEATURE DISTRIBUTION OF A FEATURE Feature distribution. Feature distribution. The distribution of a feature over its range, with value on the horizontal axis and frequency on the vertical axis. For string and categorical encoded integers, the feature distribution is displayed as a bar chart withthe highest, i.e.,
PELTARION | IMAGE SEGMENTATION BEST PRACTICES This tutorial will show you how to build a model that will solve an image segmentation problem. This means that your experiment is about partitioning an image into PELTARION | TEXT CLASSIFICATION | CONTACT US We are eager to help. As a registered user, the Peltarion team is always close by and ready to help answer your questions via our messaging service, our Slack channel or an BERT - TEXT CLASSIFICATION / CHEAT SHEET - PELTARION Sentiment analysis (😃 or 😱 or 😡 or 😍 or ) Try yourself: HappyDB - happy moments is a corpus of more than 100,000 happy moments.. Ticket classification. Save time and enable a quicker response by classifying incoming customer service requests as a first step, e.g., by topic, or urgency. BINARY CROSSENTROPY LOSS FUNCTION Binary crossentropy. Binary crossentropy is a loss function that is used in binary classification tasks. These are tasks that answer a question with only two choices (yes or no, A or B, 0 or 1, left or right). Several independent such questions can be answered at the same time, as in multi-label classification or in binary image segmentation.
PELTARION - THE OPERATIONAL AI PLATFORMPLATFORMSTORIESUSE CASESLEARNBLOGABOUT US Our Faster AI course is created for users who have no prior knowledge of AI. After completing seven short modules, users will be able to design and tweak their own AI models on the Peltarion platform. With text similarity, you can build models that compare and find texts thatare
ABOUT PELTARION
At Peltarion, the entire point of our work is to get our clients up to speed, to make it easy to start working with AI. We started working with AI and neural networks in 2004. At first, this came in the shape of two recent graduates of the Royal Technical Institute in Stockholm, Luka Crnkovic-Friis and Måns Erlandson.PELTARION PLATFORM
Peltarion is an AI platform based on deep learning where you can build, train, and deploy artificial intelligence models on your own. No Python or any code. PELTARION | BREAKING LANGUAGE BARRIERS WITH MULTILINGUAL NLP Breaking language barriers with multilingual NLP. Natural language processing (NLP) techniques aim to automatically process, analyze and manipulate language data like speech and text. The Peltarion platform enables a wide range of text solutions through our integrated language models (BERT, USE, XLM-R). Learn more about our language models. PELTARION | TURN SPEECH-TO-TEXT INTO ACTION The need for speech to text solutions are growing, and the use cases go far beyond transcription. Complaint analysis, call categorization, risk mitigation, and customer service are just a few examples of areas where businesses can benefit from speech to text solutions. 17 WAYS TO REACH THE UN'S SUSTAINABLE GOALS WITH AI Here’s what AI can do to help humanity reaching the UN’s 17 Sustainable Development Goals: SDG 01 / No poverty. With AI, we can learn to predict and prevent extreme climate-related events. To reduce vulnerability and exposure, also reducing poverty. BERT TEXT CLASSIFICATION NLP TUTORIAL Solve a text classification problem with BERT. In this tutorial, you will solve a text classification problem using BERT (Bidirectional Encoder Representations from Transformers). The input is an IMDB dataset consisting of movie reviews, tagged with either positive or negative sentiment – i.e., how a user or customer feels about themovie.
POISSON LOSS FUNCTION The poisson loss function is used for regression when modeling count data. Use for data follows the poisson distribution. Ex: churn of customers next week. The loss takes the form of: L ( y, y ^) = 1 N ∑ i = 0 N ( y ^ i − y i l o g y ^ i) L (y, \hat {y}) = \frac {1} {N} \sum_ {i=0}^ {N} ( {\hat {y}}_i - PELTARION AWARDED RESEARCH FUNDING FOR BUILDING STATE-OF We're very excited to announce that Peltarion has been awarded funding from the Swedish research institute, Vinnova, for building a Swedish language model based on state-of-the-art NLP techniques.This project is to take place over the course of the next three years, together with Research Institutes of Sweden (RISE), AI Innovation of Sweden, Swedish Agency for Economic and Regional Growth MEAN SQUARED LOGARITHMIC ERROR (MSLE) True value Predicted value MSE loss MSLE loss; 30. 20. 100. 0.02861. 30000. 20000. 100 000 000. 0.03100. Comment. big difference. smalldifference
PELTARION - THE OPERATIONAL AI PLATFORMPLATFORMSTORIESUSE CASESLEARNBLOGABOUT US Our Faster AI course is created for users who have no prior knowledge of AI. After completing seven short modules, users will be able to design and tweak their own AI models on the Peltarion platform. With text similarity, you can build models that compare and find texts thatare
ABOUT PELTARION
At Peltarion, the entire point of our work is to get our clients up to speed, to make it easy to start working with AI. We started working with AI and neural networks in 2004. At first, this came in the shape of two recent graduates of the Royal Technical Institute in Stockholm, Luka Crnkovic-Friis and Måns Erlandson.PELTARION PLATFORM
Peltarion is an AI platform based on deep learning where you can build, train, and deploy artificial intelligence models on your own. No Python or any code. PELTARION | BREAKING LANGUAGE BARRIERS WITH MULTILINGUAL NLP Breaking language barriers with multilingual NLP. Natural language processing (NLP) techniques aim to automatically process, analyze and manipulate language data like speech and text. The Peltarion platform enables a wide range of text solutions through our integrated language models (BERT, USE, XLM-R). Learn more about our language models. PELTARION | TURN SPEECH-TO-TEXT INTO ACTION The need for speech to text solutions are growing, and the use cases go far beyond transcription. Complaint analysis, call categorization, risk mitigation, and customer service are just a few examples of areas where businesses can benefit from speech to text solutions. 17 WAYS TO REACH THE UN'S SUSTAINABLE GOALS WITH AI Here’s what AI can do to help humanity reaching the UN’s 17 Sustainable Development Goals: SDG 01 / No poverty. With AI, we can learn to predict and prevent extreme climate-related events. To reduce vulnerability and exposure, also reducing poverty. BERT TEXT CLASSIFICATION NLP TUTORIAL Solve a text classification problem with BERT. In this tutorial, you will solve a text classification problem using BERT (Bidirectional Encoder Representations from Transformers). The input is an IMDB dataset consisting of movie reviews, tagged with either positive or negative sentiment – i.e., how a user or customer feels about themovie.
POISSON LOSS FUNCTION The poisson loss function is used for regression when modeling count data. Use for data follows the poisson distribution. Ex: churn of customers next week. The loss takes the form of: L ( y, y ^) = 1 N ∑ i = 0 N ( y ^ i − y i l o g y ^ i) L (y, \hat {y}) = \frac {1} {N} \sum_ {i=0}^ {N} ( {\hat {y}}_i - PELTARION AWARDED RESEARCH FUNDING FOR BUILDING STATE-OF We're very excited to announce that Peltarion has been awarded funding from the Swedish research institute, Vinnova, for building a Swedish language model based on state-of-the-art NLP techniques.This project is to take place over the course of the next three years, together with Research Institutes of Sweden (RISE), AI Innovation of Sweden, Swedish Agency for Economic and Regional Growth MEAN SQUARED LOGARITHMIC ERROR (MSLE) True value Predicted value MSE loss MSLE loss; 30. 20. 100. 0.02861. 30000. 20000. 100 000 000. 0.03100. Comment. big difference. smalldifference
AI AND DEEP LEARNING SOLUTIONS IN INSURANCE How AI and deep learning will improve customer-facing processes, risk assessment and backend efficiencies in the insurance industry PELTARION | TEXT CLASSIFICATION DATA AND PREPARATION The Peltarion Platform is an operational AI platform for building and deploying AI models that is capable of executing a broad range of deep learning-based use cases. PELTARION | TEXT CLASSIFICATION BEST PRACTICES In this tutorial, you will solve a text classification problem using BERT (Bidirectional Encoder Representations from Transformers). The input is an IMDB dataset consisting of movie reviews, tagged with either positive or negative sentiment – i.e., how a user or customer feels about the movie. PELTARION | IMAGE CLASSIFICATION BEST PRACTICES Save training time and create well-performing models with small datasets. Sounds good? This tutorial will teach you how. By using transfer learning with our pretrained snippets, you can create a well-performing model even though you have a small dataset. PELTARION | TEXT CLASSIFICATION | CONTACT US We are eager to help. As a registered user, the Peltarion team is always close by and ready to help answer your questions via our messaging service, our Slack channel or an PELTARION | IMAGE SEGMENTATION BEST PRACTICES This tutorial will show you how to build a model that will solve an image segmentation problem. This means that your experiment is about partitioning an image into PELTARION | SENTIMENT ANALYSIS BEST PRACTICES Natural Language Processing (NLP) is a field within AI that aims to understand the way humans communicate with each other and how to build systems capable of replicating that behavior. BINARY CROSSENTROPY LOSS FUNCTION Binary crossentropy. Binary crossentropy is a loss function that is used in binary classification tasks. These are tasks that answer a question with only two choices (yes or no, A or B, 0 or 1, left or right). Several independent such questions can be answered at the same time, as in multi-label classification or in binary image segmentation.
PELTARION | IMAGE REGRESSION BEST PRACTICES This tutorial will show you how to build a model that will solve a regression problem. That is a problem where you want to predict aquantity.
SINGLE-LABEL CLASSIFICATION CHEAT SHEET Use this cheat sheet. If your input data consists of labeled images containing exactly one of multiple classes. This is called single-label classification. Example use cases. Note. Disclaimer. Please note that data sets, models and other content, including open source software, (collectively referred to as "Content") providedand/or suggested
ABOUT PELTARION
At Peltarion, the entire point of our work is to get our clients up to speed, to make it easy to start working with AI. We started working with AI and neural networks in 2004. At first, this came in the shape of two recent graduates of the Royal Technical Institute in Stockholm, Luka Crnkovic-Friis and Måns Erlandson. 17 WAYS TO REACH THE UN'S SUSTAINABLE GOALS WITH AI Here’s what AI can do to help humanity reaching the UN’s 17 Sustainable Development Goals: SDG 01 / No poverty. With AI, we can learn to predict and prevent extreme climate-related events. To reduce vulnerability and exposure, also reducing poverty. BERT TEXT CLASSIFICATION NLP TUTORIAL Solve a text classification problem with BERT. In this tutorial, you will solve a text classification problem using BERT (Bidirectional Encoder Representations from Transformers). The input is an IMDB dataset consisting of movie reviews, tagged with either positive or negative sentiment – i.e., how a user or customer feels about themovie.
PELTARION AWARDED RESEARCH FUNDING FOR BUILDING STATE-OF We're very excited to announce that Peltarion has been awarded funding from the Swedish research institute, Vinnova, for building a Swedish language model based on state-of-the-art NLP techniques.This project is to take place over the course of the next three years, together with Research Institutes of Sweden (RISE), AI Innovation of Sweden, Swedish Agency for Economic and Regional GrowthDATASET FEATURES
A feature set consists of features that you want to group for use in the Input or Target block (it is possible to create a feature set with only one feature, but then it’s much simpler to use the feature as it is). The feature sets are shown above the dataset features in theDataset view.
BANK MARKETING DATASET FOR CLASSIFICATION Bank marketing. Bank marketing. The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe to a term deposit (variable y). This dataset is used in the tutorial Buyor not /
A DEEP DIVE INTO MULTILINGUAL NLP MODELS An alternative approach is to train a multilingual model, that is, a single model that can handle multiple languages simultaneously. This would circumvent having to train a monolingual model for every single language, and recent results suggest that multilingual models can even achieve better performance than monolingual models, especially for low-resource languages. SINGLE-LABEL CLASSIFICATION CHEAT SHEET Use this cheat sheet. If your input data consists of labeled images containing exactly one of multiple classes. This is called single-label classification. Example use cases. Note. Disclaimer. Please note that data sets, models and other content, including open source software, (collectively referred to as "Content") providedand/or suggested
USING AI WEATHER PREDITIONS TO BALANCE ENERGY PRODUCTION Unlike gas, electricity can’t be stored in large quantities, and thus the ordered demand and supply must balance every day. With wind energy, both the demand and the supply – the wind itself – can be better predicted with stronger weather forecasting, thanks to AI. FEATURE DISTRIBUTION OF A FEATURE Feature distribution. Feature distribution. The distribution of a feature over its range, with value on the horizontal axis and frequency on the vertical axis. For string and categorical encoded integers, the feature distribution is displayed as a bar chart withthe highest, i.e.,
ABOUT PELTARION
At Peltarion, the entire point of our work is to get our clients up to speed, to make it easy to start working with AI. We started working with AI and neural networks in 2004. At first, this came in the shape of two recent graduates of the Royal Technical Institute in Stockholm, Luka Crnkovic-Friis and Måns Erlandson. 17 WAYS TO REACH THE UN'S SUSTAINABLE GOALS WITH AI Here’s what AI can do to help humanity reaching the UN’s 17 Sustainable Development Goals: SDG 01 / No poverty. With AI, we can learn to predict and prevent extreme climate-related events. To reduce vulnerability and exposure, also reducing poverty. BERT TEXT CLASSIFICATION NLP TUTORIAL Solve a text classification problem with BERT. In this tutorial, you will solve a text classification problem using BERT (Bidirectional Encoder Representations from Transformers). The input is an IMDB dataset consisting of movie reviews, tagged with either positive or negative sentiment – i.e., how a user or customer feels about themovie.
PELTARION AWARDED RESEARCH FUNDING FOR BUILDING STATE-OF We're very excited to announce that Peltarion has been awarded funding from the Swedish research institute, Vinnova, for building a Swedish language model based on state-of-the-art NLP techniques.This project is to take place over the course of the next three years, together with Research Institutes of Sweden (RISE), AI Innovation of Sweden, Swedish Agency for Economic and Regional GrowthDATASET FEATURES
A feature set consists of features that you want to group for use in the Input or Target block (it is possible to create a feature set with only one feature, but then it’s much simpler to use the feature as it is). The feature sets are shown above the dataset features in theDataset view.
BANK MARKETING DATASET FOR CLASSIFICATION Bank marketing. Bank marketing. The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe to a term deposit (variable y). This dataset is used in the tutorial Buyor not /
A DEEP DIVE INTO MULTILINGUAL NLP MODELS An alternative approach is to train a multilingual model, that is, a single model that can handle multiple languages simultaneously. This would circumvent having to train a monolingual model for every single language, and recent results suggest that multilingual models can even achieve better performance than monolingual models, especially for low-resource languages. SINGLE-LABEL CLASSIFICATION CHEAT SHEET Use this cheat sheet. If your input data consists of labeled images containing exactly one of multiple classes. This is called single-label classification. Example use cases. Note. Disclaimer. Please note that data sets, models and other content, including open source software, (collectively referred to as "Content") providedand/or suggested
USING AI WEATHER PREDITIONS TO BALANCE ENERGY PRODUCTION Unlike gas, electricity can’t be stored in large quantities, and thus the ordered demand and supply must balance every day. With wind energy, both the demand and the supply – the wind itself – can be better predicted with stronger weather forecasting, thanks to AI. FEATURE DISTRIBUTION OF A FEATURE Feature distribution. Feature distribution. The distribution of a feature over its range, with value on the horizontal axis and frequency on the vertical axis. For string and categorical encoded integers, the feature distribution is displayed as a bar chart withthe highest, i.e.,
PELTARION PLATFORM
Peltarion is an AI platform based on deep learning where you can build, train, and deploy artificial intelligence models on your own. No Python or any code. PELTARION | BREAKING LANGUAGE BARRIERS WITH MULTILINGUAL NLP Breaking language barriers with multilingual NLP. Natural language processing (NLP) techniques aim to automatically process, analyze and manipulate language data like speech and text. The Peltarion platform enables a wide range of text solutions through our integrated language models (BERT, USE, XLM-R). Learn more about our language models. AI AND DEEP LEARNING SOLUTIONS IN MANUFACTURING How to tap into the true intelligence of all your machines. Manufacturing is primed for AI from a variety of perspectives. In core manufacturing operations such as the production line, AI can automate tasks, optimize capacity, reduce the number of defects and ensure machines are working. PELTARION | TURN SPEECH-TO-TEXT INTO ACTION The need for speech to text solutions are growing, and the use cases go far beyond transcription. Complaint analysis, call categorization, risk mitigation, and customer service are just a few examples of areas where businesses can benefit from speech to text solutions. AI AND DEEP LEARNING SOLUTIONS IN RETAIL AI and deep learning bring retail companies momentous insights on customers and profound new ways to support improved customer experience. AI can bring ease of personalization, enhanced logistics and more sustainable manufacturing processes optimized for less waste. AI AND DEEP LEARNING SOLUTIONS IN INSURANCE How AI and deep learning will improve customer-facing processes, risk assessment and backend efficiencies in the insurance industry PELTARION | SENTIMENT ANALYSIS DATA AND PREPARATION The Peltarion Platform is an operational AI platform for building and deploying AI models that is capable of executing a broad range of deep learning-based use cases. PELTARION | TEXT CLASSIFICATION BEST PRACTICES In this tutorial, you will solve a text classification problem using BERT (Bidirectional Encoder Representations from Transformers). The input is an IMDB dataset consisting of movie reviews, tagged with either positive or negative sentiment – i.e., how a user or customer feels about the movie. PELTARION | SENTIMENT ANALYSIS BEST PRACTICES Natural Language Processing (NLP) is a field within AI that aims to understand the way humans communicate with each other and how to build systems capable of replicating that behavior. SINGLE-LABEL CLASSIFICATION CHEAT SHEET Use this cheat sheet. If your input data consists of labeled images containing exactly one of multiple classes. This is called single-label classification. Example use cases. Note. Disclaimer. Please note that data sets, models and other content, including open source software, (collectively referred to as "Content") providedand/or suggested
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ADVANCED AI MADE EASY THE PELTARION PLATFORM IS AN INTUITIVE AI TOOL WHERE YOU CAN EASILY BUILD, TRAIN AND DEPLOY DEEP LEARNING MODELS WITHOUT THE NEED TO WRITE A SINGLE LINE OF CODE TRY FOR FREE BOOK A DEMO*
INTUITIVE NO-CODE AI Build your own AI models or use our pre-trained ones. Just drag & drop, even the cutting-edge ones!*
ALL IN ONE PLACE
Own the whole development process from building, training, tweaking to deploying AI. All under one hood.*
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EMPOWER YOUR TEAM
Operationalize AI and drive business value, with the help of ourplatform.
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EASY DATA UPLOAD
Start right away by uploading your own data files into the platform, or use one of the existing datasets from our Data Library. You can use tabular, text, image, audio or a combination of data types to shapeyour models.
Try for free Book a demo PRE-TRAINED NEURAL NETWORKS The platform’s prebuilt & pre-trained neural networks remove some of the main barriers for successfully adopting deep learning. The Experiment wizard gives you automatic snippet suggestions based on your input data and problem type. Try for free Book a demoVISUALIZE RESULTS
The platform evaluation view allows you to see how your model is performing in real-time during training. Graphs and metrics are automatically adjusted to your problem type for a bettervisualization.
Try for free Book a demo ONE-CLICK DEPLOYMENT AND DEPLOYMENT API Once you are satisfied with your results, you can deploy your model into production directly from the platform with one click. You can also deploy your model directly into your application via a Rest-API or one of our prebuilt connectors. Try for free Book a demo What our customers sayUser in Sports
6 days ago
"Amazing No-Code Tool" What do you like best? Peltarion is truly an amazing no code tool for for creating models and POC's. I had the great chance to be guided by Korey and Björn during a lecture with our class last week which was amazing!The many examples and the community is great for learning! What do you dislike? So far I have no dislikes - I need more experience to find the platforms limitations. What problems are you solving with the product? What benefits have you realized? Imageclassification
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Consultant in Research6 days ago
"Best low code tool I've tried" What do you like best? I'm coding on an fundamental level and genuinely appreciate this low code tool, how accessible and helpful it is when in need of analyzing/visualizing data. What do you dislike? I feel like Peltarion as a function and platform is evolving at such speed, I'm only intrigued to see how it develops and grows. I don't think the tools are the easiest to use, so I'd say a course is needed if you're a beginner like me. However, the classes are excellent and easy to follow along. What problems are you solving with the product? What benefits have you realized? I used Peltarion for both image recognition, predictions within an AI project and for presenting the data through visualization.Read more
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Valeriia M.
May 29
"Great platform for experimenting, prototyping, testing andvalidating!"
What do you like best? - Intuitive interface- tutorials- ease of using - customer support What do you dislike? - it says "no code" platform, but if one doesn't know code at all - it is quite challenging because in order to build more advanced models you need to have this knowledge. What problems are you solving with the product? What benefits have you realized? I work with AI business cases, so prototyping and experimenting are quite important for me. Peltarion is a great platform for that. I haven't found something yet that matches my needs in this aspect apart from this platform.Read more
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Consultant in Management ConsultingMay 27
"Great for AI MVP's & POC's" What do you like best? I love Peltarion and how easy it is to learn the platform. There are many great tutorials and walkthroughs in Peltarions youtube channel and I've always gotten help quickly when I've reached out. I think the platform is brilliant for building MVP's and POC's for AI projects. I've just started using Peltarion but so far it's very convenient. What do you dislike? I can't think of any downsides with Peltarion. But for improvements, I would have loved to be able to customize the user interface for the AI models and get an imbement for websites and applications. Recommendations to others considering the product: I recommend Peltarion for AI Consultants and Business Developers that would like to learn more about AI and create AI prototypes and MVP's. It's easy to learn, use and has many different solutions as well as sample datasets. What problems are you solving with the product? What benefits have you realized? I've created image recognition programs and churn prediction models with Peltarion. The most significant benefits are the many use cases!Read more
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Lucas A.
May 27
"ML made accessible!" What do you like best? The thing i love the most about Peltarion is the very helpful people behind the platform. They are always keen on helping out whenever questions arise. What do you dislike? There isn't much to dislike at all! But for me, it took a little time to get used to and learn about the UI. But once familiar, it's brilliant. What problems are you solving with the product? What benefits have you realized? I personally am not solving problems. I am rather using it to explore and play around just to get more familiar with ML.Read more
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Pontus A.
May 13
"An excellent execution in the AI/ML landscape" What do you like best? AI and ML can be overwhelming and highly technical for those who are not working in the industry daily. Peltarion's no-code approach provides a unique opportunity for those individuals to open the door to these verticals. A multitude of guides, a responsive support team, and a budding ecosystem all come together to support a wide range of users, from the inexperienced to expert data scientists.Through its robust platform, Peltarion enables quick and efficient execution of new and mature ideas alike allowing innovators and the curious to execute in the shortest epochs possible. What do you dislike? Fully utilizing Peltarion will ultimately require some degree of understanding of data science. Fortunately, there are many resources and tools which the company is and has produced to create a library, unique on the internet, to this type of no-code/low-code AI development. What problems are you solving with the product? What benefits have you realized? I used Peltarion to integrate an AI back-end to a crime-focused app I developed with a friend in my free time. The process was simple and easy for creating the proof of concept we were after.Read more
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Antimo M.
April 21
"A Complete AutoML Platform for E2E ML Applications" What do you like best? AutoML features for structured data and image and Integration with other No-Code Platform such as Bubble.io What do you dislike? The web IDE for ML is not very easy to use and understand. What problems are you solving with the product? What benefits have you realized? I created E2E Machine Learning App from building model to customer-user interface to consume itRead more
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Filip R.
March 16
"My go to tool for ML-prototyping" What do you like best? It is super easy to upload data and get started with building your AI model, and also to implement the models. This is key for me as an AI Business Consultant when making prototypes. What do you dislike? I have not found anything at the moment that I dislike. What problems are you solving with the product? What benefits have you realized? I have used it for making prototypes for churn prediction and predictive maintenance.Read more
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