Machine learning is a way that helps professionals in analyzing data, which automates the analytical model development. Businesses are massive producers of big data, and as the data is being continuously produced, machine learning solutions are frequently adapted autonomously. Here, the technology learns from new information and the old processes.
Businesses handling big data understand the significance of machine learning today. If a company wants to achieve something bigger out of business data with automation processes, machine learning consulting services help in getting successful results.
All the technologies related to machine learning algorithms tend to change faster than ever and making it harder for businesses to keep up with the technology. The change must do within the company culture by encouraging partnerships between the different industry sectors and the shared data used for the successful implementation of machine learning.
Business teams need to identify the issues they want to encounter if they are in a mood of handling machine learning projects. They should precisely define the objective of the company. For instance, the aim of boosting online sales by a specific percentage is different from the particular need to increase online sales percentage, which is done by monitoring the number of visitors.
Data quality matters a lot in the case of machine learning. Premium data allows machine learning tools to function efficiently. If any business selects a supervised learning model, the source data requires labeling. This way, the algorithm can figure out how to foresee the correct exit label. If the company chooses an unsupervised learning model, it will expel the need for labeled data. However, for efficient results, it has to be real and 100% reliable.
You must know that the platform is the most profitable investment in a machine learning project. Data scientists and professionals recommend using one fully-integrated tool like Google Cloud platform for reliable results.
Prioritize simplicity whenever possible. A simple machine learning project is better than working on expensive and most complex neural networks.
It is advisable to start small. When you take step by step progress, your business objectives are well executed and refined until the team is ready to handle more significant machine learning projects.
If the IT team undertakes the project alone, the efficiency of the machine learning project gets affected. Businesses can make the best multidisciplinary teams by bringing the different business areas together in the affected processes for the project's success. These teams will determine the best methods to achieve company objective with the following steps:
Artificial Intelligence and Machine Learning bridge the gap between brands to make proper decisions in the marketing world. They are also shaping our routine lives and decision-making capabilities. Machine learning is just an element of AI in which a computer is programmed to self-assess and enhance its performance on a specific task or project. It is more like analyzing big data.
Teachers have to play different roles, such as educators, diplomats, counselor, mentor, analyst, referee, ally, and more. There is no program or computer to meet these responsibilities, but it is now happening with machine learning.
Machine learning allows programming of the computer to determine individual study plans that meet students' needs. Algorithms can provide analysis for test results, which saves more time for teachers.
Legal firms are turning towards ML strategies for legal precedents. With the help of such programs, lawyers can review documents and previous cases within a jiffy.
Machine Learning and AI play a major role in healthcare, and doctors are using it for instant diagnosis processes. Many hospitals are applying machine learning AI algorithms to detect cancer and tumors in radiology scans and biopsy reports.
In the coming future, we can expect automated modern homes. You can be somewhere else and make your home cozier to welcome you by turning the AC on, dimming the lights, and tuning to your favorite music as you step in the house. Yes, Machine Learning is capable of everything.
Dairy Delivery Software
Native Milk always had to deal with route optimization to maximize profit and frequent changing of delivery boys. While this was easily manageable manually in offline business, it was a big headache when their business went digital.
We developed a mobile application for the drivers with route optimization. The total delivery area is divided into various routes and orders are sorted according to different routes. A driver is then assigned a single route.
PlanTech, (Construction Project Management software Case Study) a well-established US based construction company with huge projects, needed an improvement of their business processes and better optimization of their resources. As their business expanded, projects continuously got delayed which resulted in lawsuits by unhappy clients. We faced a variety of challenges to develop niche technological solutions for a company involved in the construction industry.
We designed separate web and mobile applications for foremen i.e. project managers and for construction staff (labourers). The applications has synchronized features such as calendar, attendance etc. that were updated real time Simple user interface for the layman was developed after many iterations and approval from the client.
We developed a dedicated central project management panel. The purpose was to have a centralised system update where all team leaders from different departments could update on their tasks at work.
We needed a fast technology to synchronize the source data to our system.
We had to run our programs real time during the horse race.
We ran our calculations on the given data, but by the time we generated an analysis of the probable winner, the market trends and positions of the race horses altered so our result had no value.
The reason behind using node.js is that we were able to establish a swift and persistent connection between betfair and our algorithm.
We could run our program with race data and generate results using the latest trends up-to-the-second with more than 99 % of the source data matching with our index.
On-Demand Delivery App
The client was clear with their needs but was not tech savvy enough to state specific requirements.
In GetIt the driver and vendor are treated as separate entities unlike a regular taxi application where such division does not exist.
We initiated brainstorming sessions with the client to plan out the project.
We built application functionality to optimize the process while simultaneously taking all stakeholders into account.
The client had an understanding of NFC but they had no idea of how the technology behind NFC works.
The client needed a secure platform as they wanted to keep the customer data secured.
We did a knowledge transfer with the client and explained the technology behind NFC and QR code.
We undertook a variety of security measures to prevent any leakage of user data.
The oldest insurance company of Lebanon reached out to us. They needed to digitize their operations and develop a lending application.
The target customers of the bank were mostly laymen with not much technical know-how. They consisted of old people, rural families, middle class urban families etc. Thus digitization was a challenge.
We developed a mechanism for the bank to directly disburse the loan amount to the customer’s bank account. This saved a trip to the bank of the customer and saved a lot of time for both the parties.