Tesseract TechnoLabs

Tesseract TechnoLabs Tesseract is a global end-to-end AI and machine learning service provider.

Tesseract can help you to grow your business by creating custom predictive model to predict customer's behavior and get ...
09/05/2023

Tesseract can help you to grow your business by creating custom predictive model to predict customer's behavior and get detail analysis of the customer acquisition.

May the divine blessings of Lord Ram fill your life with joy and prosperity. Tesseract TechnoLabs wishes you a very Happ...
30/03/2023

May the divine blessings of Lord Ram fill your life with joy and prosperity. Tesseract TechnoLabs wishes you a very Happy Ram Navmi! On this auspicious occasion, let's reflect on Lord Ram's teachings of righteousness, compassion, and valor. As we celebrate the festival of Ram Navmi, let us strive to imbibe these values in our personal and professional lives.

At Tesseract TechnoLabs, we are committed to leveraging technology to make a positive impact on society. As we celebrate Ram Navmi, let us take inspiration from Lord Ram's journey and use our skills and knowledge to create innovative solutions that benefit humanity. Let us work together towards building a better and brighter future for all.

On this joyous occasion, we express our gratitude to all our clients, partners, and employees for their unwavering support and trust in our services. We look forward to continuing our journey of excellence and innovation with you. Once again, Tesseract TechnoLabs wishes you a very Happy Ram Navmi!

Humans are good at analysis, but machines are better at this. Humans, do not only analyze things, but we also create new...
19/12/2022

Humans are good at analysis, but machines are better at this. Humans, do not only analyze things, but we also create new things, so we are good at creating new things.

But machines are just starting to get good at creating sensical and beautiful things. This new category is called “Generative AI,” meaning the machine is generating something new rather than analyzing something that already exists.

Generative AI is well on the way to becoming not just faster and cheaper, but better in some cases than what humans create by hand. Every industry that requires humans to create original work—from social media to gaming, advertising to architecture, coding to graphic design, product design to law, marketing to sales—is up for reinvention.

Shallow leaners mostly depend on the features used to create the prediction model. On the other hand, deep learners have...
21/11/2022

Shallow leaners mostly depend on the features used to create the prediction model. On the other hand, deep learners have the potential to extract better representations from raw data and create much better models.

Using a standard machine learning approach, we would have to manually select relevant features of the image, such as edges or corners, in order to train the machine learning model. The model then refers to these elements when analyzing and classifying new objects.

With a deep learning workflow, relevant features are automatically extracted from images. In addition, deep learning performs "end-to-end learning"—where the network is given raw data and a task to perform, such as classification, and learns how to do it automatically.

So feature engineering, which is a hard thing, can increase the performance of a shallow learner, but in a deep learning environment, feature engineering is integral.

Another key difference is that deep learning algorithms scale with data, while shallow learning converges. Shallow learning refers to machine learning methods that stabilize at a certain level of performance as you add more examples and training data to the network.

There are 4 main techniques in machine learning, which are explained below1. Supervised learning: Supervised learning is...
16/11/2022

There are 4 main techniques in machine learning, which are explained below

1. Supervised learning: Supervised learning is a type of machine learning in which machines are trained using well-labeled training data, and based on that data, the machines predict the output. Labeled data means that some input data is already labeled with the correct output.

2. Unsupervised learning: As the name suggests, unsupervised learning is a machine learning technique in which models are not supervised using a training dataset. Instead, the models themselves find hidden patterns and insights from the given data. It can be compared to learning which takes place in the human brain while learning new things.

3. Semi-Supervised learning: Semi-supervised learning is a broad category of machine learning that uses labeled data to base predictions and unlabeled data to learn the shape of a larger data distribution.

4. Reinforcement learning: Reinforcement learning is all about making decisions sequentially. In simple words, we can say that the output depends on the state of the current input and the next input depends on the output of the previous input.

Become a Spatial Data Scientist
14/11/2022

Become a Spatial Data Scientist

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Ahmedabad
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