Machine learning is an unquantifiable course that has lots of significance (Even though it is a subcategory of Data Science i.e. Intelligent Retrieval). You get to dive into this excellent course and decide whether you want to have a career in data science learning Machine Learning “ML”. Starting early should give you a head start and the earlier you start – you get a better chance at exploring things and developing a deep understanding of the internals and a deep understanding of it will make you an expert. Many undergraduates ask how do I start learning and what are the steps to take in machine learning.
The following are steps steps guides to Machine Learning taken from https://machinelearningmastery.com/
Step 1: Adjust Mindset. Believe you can practice and apply machine learning. …
Step 2: Pick a Process. Use a systemic process to work through problems. …
Step 3: Pick a Tool. Select a tool for your level and map it onto your process.
Step 4: Practice on Datasets. Select datasets to work on and practice the process
Step 5: Build a Portfolio. Gather results and demonstrate your skills.
The advantage of machine learning is the prognostic and representations that make predictions. To be great at “Machine Learning you have to be able to solve real-life problems. This process should be followed orderly.
According to Colleen-Farrelly’s answer to a post on quora, she suggested starting with the basic math courses as your electives: multivariable calculus, linear algebra, and an undergraduate probability and statistics course. These will give you a strong enough foundation to start diving into the algorithms with a fair understanding of their pieces and the possible consequence of using the algorithm on data. Elements of Statistical Learning is a great text that provides theoretical material and hands-on applications on R (along with a solutions manual).
When it comes to careers in computer science, it is a must for striving developers to work on their own projects. Developing real-world projects is the best way to put a point on your skills and merge your knowledge into practical experience. The more you experiment with different projects, the vaster you are in it.
Below are some of the machine learning projects that can help undergraduates kick start their Machine Learning journey.
1| Sentiment Analysis of Product Reviews
About: Sentiment analysis is the use of processing language, analyzing text, structuring, and biometrics to orderly identify, extract, quantify, and study affective states and subjective information. (Google)
2| Stock Prices Prediction
About: Stock Price Prediction in machine learning helps to discover the future value of stocks and other properties traded on foreign exchange. The entire idea of predicting stock prices is to gain significant profits. Predicting how the stock market will perform is a hard task to do.
3| Sales Forecasting
About: The aim of sales forecasting is to vaticinate the future demand for products or services. Some typical alterable used in sales forecasting are past sales data, website visits, economic trends, climates, etc.
4| Movie Ticket Pricing Prediction
About: Machine learning can be used to procure or produce individualized services, such as pricing, which can be used for booking movie ticket.
5| Fake News Detection
About: In this project, one can use a machine learning to detect fake news in an article posted in a b log site.
6| Sports Prediction
About: Machine Learning can be used to predict match results to understand the odds of winning or losing and it shows the performance of the teams. This makes stakeholders understand the odds of winning or losing.
7| Object Detection
About: One of the fundamental computer vision problems, object detection provides valuable information for semantic understanding of images and videos, and has many applications in image classification, human behavior analysis, among others.
8| Disease Prediction
About: Machine learning algorithms can be used to look for predictions on traditional and modern diseases.
9| Prepare ML Algorithms – From Scratch!
About: You can begin choosing an algorithm that is straightforward and not too complex. Behind the making of each algorithm – even the simplest ones – there are several carefully calculated decisions. For instance, you could take a vanilla logistic regression algorithm and add regularization parameters to it to transform it into a lasso/ridge regression algorithm.
10| Develop a Sentiment Analyzer
About: Machine Learning can be used to develop a sentiment analyzer that can predict if a given text of an article or a writers data towards a particular product is positive, negative, or neutral extracting meaning from the natural language and assigning it to a numerical score.
11| Parkinson’s project
About: The idea behind this project is to design an ML model that can differentiate between healthy people and those suffering from Parkinson’s disease.
12| Enhance Healthcare
About: Ability to help HCPs (Health Care Providers) to deliver speedy and better healthcare services but are also reducing the dependency and workload of doctors to a significant extent.
With this you can create:
- Diagnostic care systems that can automatically scan images, X-rays, etc., and provide an accurate diagnosis of possible diseases.
- Preventative care applications can predict the possibilities of epidemics such as flu, malaria, etc., both at the national and community level.
13| Mall Customers Projects
About: This Machine Learning can be created to record number of people who visited the mall in terms of gender, age, annual income, the amount spent. This algorithm can be built to differentiate customers into segments based on their behavioral expressions and attitudes as this can be used brands and marketers to improve their sales and revenue (income) and customer satisfaction.
These are some of the comprehensive lists of machine learning ideas and though, machine learning is still at an early stage throughout the world, there are lots of products and projects that need to be worked on and improved.
You can refer to our post on how to use a machine to make life easier to know what project suits you and how you can use this skill to improve the world positively.