Deep learning projects are the foundation of artificial intelligence, making the computers perform functions in the competing digital world without explicit programming. Indeed, even simple machine learning projects can work without the help of human hands but can perform the task that humans do for any business or activities. One of the machine learning project ideas which we thought can only be seen in Hollywood movies is the self-drive cars. But today, beyond our imagination deep learning projects are coming to reality. Today, human lives are facing high risks, especially to health and violence. Machine learning project examples are robust analytics and gadgets that can identify human body status and help you decide for the appropriate intervention to live. In military operations, drones and robotics powered by machine learning are taking over the dangerous jobs to life bomb diffusion to preserve the lives of military men.
Future Of Machine Learning
Nowadays, the business and marketing world is now entering the era data is the core of the competition to understand the minds and behaviors of the consumers. As time goes by, more data are added to the workflow of people in the marketing department, which requires more time and effort and resources to understand the information and stay in the competition. The ice cream giant Ben & Jerry’s launched a range of breakfast-flavored ice cream in 2017. The company uses a simple machine learning project to listen to the trend of public consumers. For example, they took data analysis of at least 50 songs that mentioned “ice cream for breakfast” and uncover the emerging trends. The deciphering of social and cultural chatter resulted in the creation of Fruit Loot, Frozen Flakes, and Cocoa Loco using cereal milk. Hence, it makes the company on top of the competition. Although economic and IT experts would say that it may be difficult to calculate the future of machine learning because it is growing so fast. But according to Forbes, the AI, and machine learning are setting a total value of $2.6 Trillion in the market while its manufacturing and supply chain is hitting a record of 2 Trillion dollars. That’s a lot of money to make the future of the technology grow, expand, and scale-up.
Machine Learning Applications Within The Supply Chain Industry
What is another interesting trend is that machine learning is leveraging the neural networks of the supply chain. It changes the market dynamics where the supply-chains are getting shorter, leaner, and making the manufacturers closer to the end-user. Marketing experts claim that by 2020 at least 95% of the supply chain vendors globally will be streamlining their operations because of the total dependence on machine learning. Recently, Microsoft and OpenAI (creator of Elon Musk) went into partnership to build deep learning projects. The partnership looks promising breakthroughs that can change the world.
Most Popular Machine Learning Projects
1. Product Bundles
One of the exciting machine learning examples where it directly identifies project bundles in a bunch of sales data. The project uses a clustering technique that is the subjective segmentation for them to get the project bundles from sales data. One of the success factors of the project is the understanding of the developers on market basket analysis.
2. Stock Price Prediction
This machine learning project becomes addictive to those working on finance domains. It can predict future stock prices. However, the challenge they face with this project is that stock prices data is granular, where they come in different types—volatility indices, rates, fundamental indicators. For newbies on the stock market, you can easily use machine learning at six months prediction to get a reasonable stock price.
3. Sales Prediction Of BigMart
A machine learning project for beginners because it is one of the easiest because of it one of the machine learning projects in phyton. The project is designed to provide predictions and finding sales of each product for a BigMart store. The datasets have 2,013 sales data of the 1,559 products across the ten store outlets. The project uses the regression model to predict the sales of each product. It is also essential to understand the visualization of sales data using Python.
4. Disease Prediction
Medical science is into machine learning projects to predict diseases. There is the Breast Cancer Wisconsin Diagnostic Dataset, where the AI can predict if it is malignant or benign breast mass. One of the vital knowledge you need when developing this machine learning idea is the random forest.
5. Human Activity Recognition System
It is a classifier of the machine learning model that can identify human fitness activities done by an individual. When developing the machine learning idea, a smartphone dataset is used. The device shall contain the fitness activity of a person that can be captured by the smartphone. Since this machine learning example is a classification problem type of AI, a beginner should develop problem-solving skills. Also, it is essential to know SVM and Adaboost.
6. Alation
Alation uses machine learning that automatically index data sources and gathers knowledge about the data. The use of the AI will increase your confidence in the usage of your data, improve productivity, and knowledge management. Moreover, it gives empowerment to employees to understand, use the right data to better and fast decision making.
7. Cinnamon AI
One of the struggles among businesses is the duplication of tasks that lead to a waste of time. In most cases, business documents are not easy to file and structure, such as Invoices and financial statements. Cinnamon AI can automate data extraction and task processing easily and fast. It reduces cost and time.
8. Promo Smart 4.0
Automatically align business objectives that help synthesize decisions across key performance indicators. Besides that, it uses advanced algorithms to determine better and profitable promos. It is end-to-end data-based analytics to envision, create, and enable the execution of business plans with efficiency. In addition, it has an intelligent search assistant that provides text or voice command to give relevant information for timely decision making.
9. Price Smart
It provides better analytics of historical transactions, the competition of prices, and market signals that can help a business enact right pricing decisions. The machine learning project can determine price elasticity, SKU level, pricing recommendation of key-valued items, and categories. Moreover, it can help business establish accurate price change experiments and low-risk store-set. As a result, you can have a better visual of price dynamics.
10. Ingraph
A machine learning system for healthcare institutions that will empower them to integrate complex data from multiple sources and provide the healthcare professionals valuable insights. This is because Ingraph can track any metrics. It can identify at-risk patients, examine high-utilization measures, cost drivers, and monitor adherence to medications.
11. Campaign 360
Do you know that marketing people are always in an argument with salespeople in your business? The fact is that they are both seeking full visibility to visualize what campaign will satisfy them to drive opportunities and make a successful campaign. Campaign 360 machine learning equips the marketers with a powerful real-time and full-funnel campaign. It gives the full picture of the possibilities when marketing campaign starts. It also helps in identifying the quality leads that the sales have not yet reached. Finally, it can be useful when you assess the performance of your campaigns. The team does not need to wait for six months to see the campaign performance. It can generate forecast and marketing potentials that the team can always grab and decide.
12. LogiNext Field
The fast globalization puts field operations management as a severe challenge. With LogiNext Field, your management towards sales force, field technicians, field service agents, medical representatives, etc. will become active. Besides that, you can track real-time schedules, work progress in real-time and activity plans.
13. VUKU
VUKU is a sophisticated machine learning tool that can be adaptable to a variety of sectors like supply chain, asset management, and fleet management. Moreover, the platform uses an advanced probability modeling technique to understand history. As a result, it can create models and outlook of possible outcomes.
14. Health And Scale Interception
Built to provide preferred networks of physicians and facilities over the needs of individual members. Also, it can help members to identify specific providers for their particular health conditions. It enables selective and targeted care pathways to reduce risks to prevent unfortunate circumstances during the early stages to increase the success of intervention and lower the cost. Hence, the data can guide in giving effective value-based treatments and pricing guide.
15. Compression.AI
A machine learning project that improves the encoding and decoding of images without losing quality. The algorithm uses the deep neural networks so it can create a representation of the image which they can Machine Learning Visual Extension. Moreover, the JPE and PNG formats are changed to deep learning neural networks to give better visual quality. With the use of this machine learning tool, it can speed up your website and application because it can accelerate the page download time because of the lowering of image file sizes. It can also increase Search Engine Optimization ranking because the fast load time can lead to increased conversion rate.
