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New KDnuggets cartoon examines what may be the worst example of telemedicine …

Originally from KDnuggets https://ift.tt/2LvPVsQ

Check out 5 new features of the latest Scikit-learn release, including the ability to visualize estimators in notebooks, improvements to both k-means and gradient boosting, some new linear model implementations, and sample weight support for a pair of existing regressors.

Originally from KDnuggets https://ift.tt/2y4j9vM

Machine learning is a hot topic of discussion nowadays. And you can find its multitude of uses across the different segments. Deep learning is an integral part of machine learning. When we talk about machine learning or deep learning, it has created quite a stir in the market. Basically, these technologies work on algorithms and programming that enables the machine to think like a human and take a decision. So what works behind them, you will learn about all this aspect in any of the machine learning training programs. Still, here, we are going to cover one of the elements that ensure the seamless working of deep learning enables technology. Yes, we are going to talk about neural networks.

We all know that machines have brains, but in recent years, we have seen some significant development in this domain, and this is because of the surge of new technologies like machine learning and deep learning. What works behind the scene is the neural network. These are designed similar to the neurons of the human brain. These neural networks work on the detangling complex relationship and unfold it to the machines so that they can perform their task.

Subsets of Machine Learning

If you have undergone machine learning training or are planning to go for a machine learning course, then you would get to know that there are subsets of machine learning and each of these subsets have the potential to form a new career for those who are willing to grow in the field of artificial intelligence. The following are the subsets of machine learning :

1. Neural network- as we have mentioned above, neural network functioning is designed similar to the human brain, with the help of this network software learns to recognize images and enables the machine to make a decision. With the help of a neural network, machines can also make predictions and decisions and that too with accuracy. But it also depends on the accuracy of the data.
2. Natural Language Processing (NLP)- It enables the machine to understand human language and interpret. As it continues to develop, machines will also learn how to respond in a similar way to humans.
3. Deep Learning- It uses machine learning tools and uses the same to solve problems and make decisions. With deep learning, the data is processed via neural networks and thus making the machine to work similarly as the human does. This applies to text, images, speech to come to a conclusion. In simple words, its objective is to make a decision similar to human beings.

What sets the neural network apart from other networks?

Well, neural networks are designed to perform on the same base as the neurons in the human brain. The functioning of a brain neuron involves receiving input and then instigates an output that is used by another neuron. The neural network security training also works on a similar pattern; they stimulate behaviour in learning about the data which is collected and then predicting outcomes.

There are three layers of neurons in the neural network:

1. Input layer
2. Hidden layer
3. Output layer

When we talk about deep neural networks, then it has many layers and the process of using all these layers is called deep learning.

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4. Deep learning with COVID-19 xray convolutional Neural Network.

Deep neural networks are complex neural networks, and they have around 1000 or more neurons per layer. The more is the number of networks, the more complex tasks it can handle. But, this might take some time for the same. In the case of the classic neural network, the information traverses in a single direction where each layer is wholly connected to neighbours.

How can neural networks create an impact on our life?

Well, in the years to come, we are going to witness a significant impact on technology. And ML is going to be an integral part of the same. Machine learning algorithms are going to be a key game-changer. Here is how it is going to change our lives in the years ahead:

1. Language barrier elimination via interpreting tools for personal use
2. Image processing and photo effects
3. Video analytics
4. Using a photo to find a person on the internet
5. IoT concept development via voice interaction interfaces
6. Self-learning system for production and device management
7. Object recognition and classification of images

Conclusion

These are few of the many ways how machine learning and its subsets, neural network, NLP and deep learning are going to impact our lives. This will inevitably lead to a growing demand for individuals who are skilled in machine learning. This field is not only going to be a great career booster but also will lead to a lot of development. Global Tech Council is providing an online machine learning training program. This program aims at imparting all the information about machine learning and its allied concepts. You can simply enrol for this program and let your career grow by leaps and bounds.

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Neural Network with Deep Learning was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

Via https://becominghuman.ai/neural-network-with-deep-learning-ff7dfbaed276?source=rss—-5e5bef33608a—4

Via https://becominghuman.ai/quantum-computing-with-q-superposition-baffc366522b?source=rss—-5e5bef33608a—4

Not every disease is fatal, we know this well. Some patients’ bodies to take up the fight against the disease with a greater chance. What just made these patients more resilient, and how can this be facilitated?

The roots of data science, just like in the case of artificial intelligence appeared in the previous century and thus become widespread in recent years. This science allows for a structured analysis of data and varieties of tools and algorithms for construing change.

The elevated level of gained knowledge thus can shed light on facts and contexts that would remain hidden from the human intellect. We can outline patterns, future scenarios that — while not equal to a prediction — can embark on the challenges of the future with more confidence.

It lends techniques from several fields, including math, statistics, and computer science.

Use cases in healthcare

Data analysis can also be used in health care to develop more advanced and effective therapies. Thereby increasing the life expectancy of the population. Data science is used in healthcare in several areas, including more accurate diagnosis, drug development, and prevention.

To be able to do this, professionals must first gather the amount of data that is sufficient to perform the analysis. The human brain and muscles produce two terabytes of data per day. This amount of data is already enough to gain insight into the hidden processes that take place in the body.

Treating cancer:

The number one public enemy is still cancer, which is projected to cause 1.8 million illnesses in the United States, of which more than 600,000 will be lethal.

A healthcare startup in Boston is developing BPM 31510, a drug that detects and triggers the natural death of cells damaged by the disease. With these drugs, the cancer cells can be removed from the human body naturally, without extensive medication and further damage to the patient’s health.

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4. Deep learning with COVID-19 xray convolutional Neural Network.

To be able to do this, BERG Health used machine learning algorithms to extract and analyze data from samples of 1,000 patients.

This kind of extensive technology use on healthcare development can help lots of people in the future, with less harm and less money spent by the patient.

Advances in health care have been able to rid humanity of many diseases, including deaths such as plague or smallpox. There are still diseases that we can’t cure for sure. Perhaps it is data science and machine learning that will bring the desired next age of development, in which we can also say goodbye to dreaded diseases like cancer.

Other use cases:

Data science and machine learning can be utilized not only in healthcare, but also in areas such as agriculture, telecommunications, or finance.

From the data obtained from the previously recorded market price movements, we can make models that result in more accurate predictions than a human can do. The repetitive patterns recognized in the data tell the financial professional when and how much to buy or sell from the asset being traded. Algorithms created with machine learning technology produce much more precise results and low degrees of drawdowns, as can be seen in the results of the bot developed by b-cube.ai fintech startup.

Don’t forget to give us your ? !

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How can data science and machine learning save lives? was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

Via https://becominghuman.ai/how-can-data-science-and-machine-learning-save-lives-e782f9003c23?source=rss—-5e5bef33608a—4

Check out 5 new features of the latest Scikit-learn release, including the ability to visualize estimators in notebooks, improvements to both k-means and gradient boosting, some new linear model implementations, and sample weight support for a pair of existing regressors.

Originally from KDnuggets https://ift.tt/2y4j9vM

AI is certainly playing an important role in our global fight against the novel coronavirus. These YouTube channels are recommended to keep you covered with the latest advancements in the field and how it is impacting our world.

Originally from KDnuggets https://ift.tt/364tvbq

The new conversational agent exhibit human-like behavior in conversations about almost any topic.

Originally from KDnuggets https://ift.tt/3bBBUUY

Via https://becominghuman.ai/top-5-applications-of-artificial-intelligence-81e52f8f08d7?source=rss—-5e5bef33608a—4

Via https://becominghuman.ai/image-blending-using-laplacian-pyramids-2f8e9982077f?source=rss—-5e5bef33608a—4