Machine learning is essentially a branch of computer science which allows computers to learn on their own without them being explicitly programmed. With the help of machine learning, systems have the capacity to learn and also improve. Mastering the machines uses techniques like information and observation. The main idea is to let computer systems carry out research robotically in the absence of human interference and human assistance. Machine learning can be used in a variety of computing jobs wherein designing or programming algorithms is not easy. Applications like email filtering, optical character recognition, detection of intruders in a network, computer vision etc are some applications which use machine learning.

Machine learning tasks can be broadly categorized into three key categories according to nature of the feedbacks or learning signals available.

Supervised Learning: Here the computer is given example inputs and desired outputs. So, facts are able to predict the output.

Unsupervised Learning: In this, no labels will be given to the learning algorithms and these must find their structure in their inputs. Unsupervised learning is either a means towards a goal or a goal by itself.

• Reinforcement Learning: Here, the computer program will interact with dynamic environments wherein it has to carry out a specific goal. So, it will produce moves and come across rewards or errors. This technique will allow the machines to determine robotically which conduct is right in a specific context in order to improve the performance.

The IoT or Internet of Things is destined to be the largest technological breakthrough in modern times. The main concept centers on sensors which are embedded in almost all kinds of appliances, ranging from clothing to mobile devices. This will enable these appliances to interact with one another. Gartner studies reveal that by 2020, numbers of units using the IoT will cross 26 billion. At the same time, many companies also understand the obstacles they will face in adopting the IoT. So, they have turned to machine learning techniques. They want to use machine learning to grasp the true potential of the Internet of Things.

The main way to make the IoT work is to ensure that the data which is getting generated by the sensors is not only collected, they are also analyzed by organizations so that these organizations can recognize the specific patterns to use the data better. And this is where machine learning will have a crucial role to play. Machine learning will focus on specific algorithms which will allow computers to “learn” without programming.

Machine learning will enable companies to handle the obstacles which make using IoT difficult. One of the most significant challenges is the volume of data being generated. This is usually huge and is expected to grow as more and more appliances get connected. Tracking such huge volumes of data can become very hard through traditional data collection and analysis methods. Machine learning will make this task simpler. It will take the huge volumes of assorted data and then learn from this. It will identify patterns or trends which businesses can then use for better sales.

Machine learning may help you remove the hindrances to adopting IoT but costs of such technologies are very high for the smaller companies. The companies will have to spend a lot of money on getting data scientists for interpreting the results. This is why machine learning-as-a-service has now come about. Now companies can actually hire MLaaS vendors for taking care of their machine learning requirements. This has also helped the small businesses to save a lot of time and money in the process. The MLaaS have better expertise and they can conduct queries much faster.

Some of the most recent IoT innovations are as follows:

The Nest is perhaps one of the most popular IoT products which refer to a smart thermostat. It has the capacity to learn family routines and it will then adjust the temperature mechanically based on whether you are at home or away, whether you are sleeping or active, with a view to conserving energy. You therefore get to save on your electricity bills. Smart homeowners will use it to manipulate their home environments and enjoy better power savings.

Similar to the Nest, there is the Phillips Hue lights which is a smart bulb that changes colors according to your phone app. You can use your smartphone to switch them on or off; you can even sync these to follow audio tracks on your phone. Many companies are coming out with these smart bulbs which are both cost-saving and entertaining at the same time.

Healthpatch Health Monitor is a convenient IoT product which helps in treatment of patients. The patients can get their ECG reading, skin temperature, coronary heart charge, fall detection etc remotely. So, doctors can also be alerted about probable health issues before these actually arise.

Wearables are another popular IoT trend which includes many devices that cover health, fitness and even entertainment areas. These sensors have to be very energy efficient and must consume low power. One such example is the tracker band which has features like food logging, activity tracking, sleep pattern tracking etc.