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Machine Learning Projects for Beginners

Machine Learning, as a career, may seem extremely attractive to most people due to the kind of salaries which are on offer for Data Scientists. However these people rarely deign to act on their impulses because they are not sure about their fit for that kind of work. The number of Machine Learning Internships are also limited in number for people who are working or in college. Thus it can remain as their biggest career "What-if" which haunts several people.
In order to help you make this decision, we have compiled a list of the best Machine Learning Projects for Beginners which will allow you to make a more informed decision about their attitude towards Machine Learning.

Datasets useful for Machine Learning Projects for Beginners

One of the most important tools that you need at your disposal in order to experiment with Machine Learning is access to huge datasets. This is where the Internet has made things extremely easy. Access to datasets of this size would have been extremely difficult even 5-10 years back however today, with the amount of data being generated especially over the Internet, the access has become extremely easy.
One thing that we need to keep in mind when we look at datasets is that the datasets do not only mean rows upon rows of numbers in excel sheets. These datasets also include images and sound samples. Some of the major open-source datasets are:

  • Image Datasets: There are several datasets where it is possible to find images of different types which can be used for Machine Learning Projects for Beginners. Some of the most prominent ones are:
    • Open Images Dataset
    • MNIST
    • ImageNet
    • Street View House Number (SVHN)
  • Natural Language Processing Datasets: This datasets is more along expected lines. It consists of excel sheets consisting of words rather than numbers. Some of the best NLP datasets are:
    • IMDB Reviews
    • Twenty Newsgroups
    • Yelp Reviews
  • Sound Processing Datasets: These datasets include the sound samples from several different sources. Some sound processing datasets available in open source are:
    • BallroomDancers.com
    • Free Music Archive
    • Free Spoken Digit Dataset

All these datasets and several more can be used in interesting Machine Learning Projects for beginners. Apart from these datasets, there are some compendiums of huge datasets which can be useful for beginners. Some of these compendiums are mentioned below:

  • UCI Machine Learning Repository (http://archive.ics.uci.edu/ml/index.php)
  • Kaggle Datasets (https://www.kaggle.com/datasets)
  • Data.gov (https://www.data.gov/)
 Some of the most intriguing projects that can be used are explained in the next section.

Machine Learning Projects for Beginners

There are several Machine Learning Projects that can be attempted by Beginner to get a better feel of the subject.

  • Machine Learning Model Fit - In this project, you can use any of the datasets from the open-source datasets available. After importing the data, it has to be cleaned and split into the training data, testing data and validation data. Following this, the different models or algorithms can be tested on the dataset to find out which model fits the data best. The benefits of this Machine Learning Projects for Beginners are:
    • Intuition for which model will fit which data
    • Familiarity with Data Preparation techniques
    • Easy to imagine
  • Sports Analytics - Sports is one of things that unifies most people in their interest. Using sports as the base ensures that this is one of those Machine Learning Projects for beginners they would enjoy. There are several datasets of sporting data available. You can parse through the data and perform several machine learning techniques in order to find the most appropriate ones as well as draw conclusions (obvious or not). There are several different sources to find sporting data:
    • Rotowire (https://www.rotowire.com)
    • CricSheet (https://cricsheet.org/downloads/)
  • Regression for Retail - There are several datasets for Walmart sales which can be used in order to learn how to properly learn regression. It may also include dimension reduction techniques such as Principal Component Analysis, Linear Discriminant Analysis, etc. It is good place to start for a beginner and can be completed is a reasonably short period of time.
  • Movielens Database - The Movielens dataset is extremely rich in terms of the number of entries as well as the genre. This dataset can be very useful as Machine Learning Projects for beginners where they can learn to learn about preparing the data in adequate format as well as building recommendation engines on these datasets.
  • Twitter Sentiment Analysis - In this project, you need to crawl the twitter database and select a certain set of it. After the tweets are collected, you have to conduct a sentiment analysis on the same. This project can be done on different brands or for identifying hate tweets. There are several other ways for which the sentiment analysis can be done. It is possible that the crawling may not provide the data necessary in which case, you can DM twitter ( @TwitterSupport) to get the data. It is also possible to conduct sentiment analysis on several other sources but twitter is ideal because of the word limit which ensures that classification of the tweet is easier.

Conclusion

These are some of the best Machine Learning Projects for Beginners as they give a good idea to the participants about what exactly their job as Machine Learning Engineers would be. It can act as the boost they require to dive deep into the topic and emerge into greener pastures.