As AI continues to progress rapidly in 2021, achieving mastery over Machine Learning (ML) is becoming increasingly important for all the players in this field. 

So, if you are a beginner, the best thing you can do is work on some Machine Learning projects. We have some great machine learning project ideas for you. 

1. Stock price predictor Businesses today are on the lookout for software that can monitor and analyze the company performance and predict future prices of various stocks. And with so much data available on the stock market, it is a hotbed of opportunities for data scientists. 

2. Sentiment Analyzer You can try to mine the data from Twitter or Reddit to get started with your sentiment analyzing machine learning project. This might be one of those rare cases of deep learning projects which can help you in other aspects as well. 

3. Enhance healthcare By harnessing healthcare data, you can create diagnostic care systems that can automatically scan images, X-rays, etc., and provide an accurate diagnosis of possible diseases. Machine learning is still at an early stage throughout the world. There are a lot of Machine Learning projects to be done, and a lot to be improved. 

Machine Learning is a subset of AI and is the scientific study of algorithms and statistical models used by computer systems. The primary aim is to allow computers to learn automatically, with no human intervention or assistance. Here are some key prerequisites for machine learning 

1. Statistics, Calculus, Linear Algebra and Probability Statistics contain tools that are used to get an outcome from data. Calculus plays an integral role in the algorithm. Linear Algebra is used in machine learning to perform operations and transform on datasets. Furthermore, the probability is also a foundation in machine learning prerequisites. 

2. Programming Knowledge: Writing code is one of the most important things when it comes to Machine Learning. You need to know languages such as Python and R to implement the process. 

3. Data Modeling It is a process of estimating the structure of the data set, and it is done to find any variations or patterns within. Machine Learning is also based on predictive modelling. If you do meet these machine learning and AI prerequisites, understanding machine learning would become much easier. 
 

AI is one of the most popular technologies on the planet, thanks to its versatility and advanced solutions. It has been growing at a fast pace, but what is the future scope of artificial intelligence? Today we take a look at the answer. 

1. Science and research AI can handle large quantities of data and processes it quicker than human minds. This makes it perfect for research where the sources contain high data volumes. AI is already making breakthroughs in this field. 

2. Cybersecurity is another field that’s benefitting from AI. As organizations are transferring their data to IT networks and the cloud, the threat of hackers is becoming more significant. Cognitive AI is an excellent example of this field. 

3. Data analysis can benefit largely from AI and ML. AI algorithms are capable of improving with iterations, and this way, their accuracy, and precision increase accordingly. AI can help data analysts with handling and processing large datasets. As AI shows massive acceleration in these fields, AI and machine learning careers are also on a rise. This makes AI a highly lucrative field for professionals to invest in.