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Edureka's Machine Learning Certification Training using Python in Melbourne, Australia, is designed to make you grab the concepts of Machine Learning. This Machine Learning Certification in Melbourne, Australia, will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in the python programming language.
Furthermore, in this Machine Learning with Python Training in Melbourne, Australia, you will be taught Reinforcement Learning, which is an essential aspect of Artificial Intelligence. You will be able to automate real-life scenarios using Machine Learning Algorithms. Towards the end of this Machine Learning Training in Melbourne, Australia, we will be discussing various practical use cases of Machine Learning with Python programming language to enhance your learning experience. Edureka offers the best Machine Learning Training in Melbourne, Australia, for those who want to be the best in Python. Enroll now with Edureka's online Machine Learning Certification in Melbourne, Australia, to train industrial experts.
Data Science is a set of techniques that enables computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within mathematics, statistics, information science, and computer science.
This Machine Learning Certification Training in Melbourne exposes you to different classes of machine learning algorithms like supervised, unsupervised, and reinforcement algorithms. This ML Training in Melbourne imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes, and Q-Learning.
Upon completion of this Machine Learning using Python Training in Melbourne, you should be able to:
Edureka's Python Machine Learning Training in Melbourne is a good fit for the below professionals:
The Python and Machine Learning training prerequisites in Melbourne include development experience with Python. Fundamentals of Data Analysis practiced over any data analysis tools like SAS/R will be a plus. However, Python would be more advantageous. You will be provided with complimentary "Python Statistics for Data Science Course" as a self-paced course once you enroll for the Machine Learning Training in Melbourne.
Edureka Machine Learning Training in Melbourne provides:
Machine Learning Certification
Edureka’s Data Scientist with proficiency in Python Certificate Holders work at 1000s of companies like
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This Machine Learning online course comprises of 34 case studies that will enrich your learning experience. In addition, we also have 3 Projects that will enhance your implementation skills. Below are few case studies which are part of this Machine Learning course online:
Python Machine Learning Training Case Study 1: Maple Leaves Ltd is a start-up company which makes herbs from different types of plants and its leaves. Currently the system they use to classify the trees which they import in a batch is quite manual. A laborer from his experience decides the leaf type and subtype of plant family. They have asked us to automate this process and remove any manual intervention from this process.
You have to classify the plant leaves by various classifiers from different metrics of the leaves and to choose the best classifier for future reference.
Machine Learning Online Training Case Study 2: BookRent is the largest online and offline book rental chain in India. Company charges a fixed fee per month plus rental per book. So, company makes more money when user rent more books.
You as an ML expert and must model recommendation engine so that user gets recommendation of books based on behavior of similar users. This will ensure that users are renting books based on their individual taste. Company is still unprofitable and is looking to improve both revenue and profit. Compare the Error using two approaches – User Based Vs Item Based
Machine Learning Online Training Case Study 3: Handle missing values and fit a decision tree and compare its accuracy with random forest classifier.
Predict the survival of a horse based on various observed medical conditions. Load the data from ‘horses.csv’ and observe whether it contains missing values. Replace the missing values by the most frequent value in each column. Fit a decision tree classifier and observe the accuracy. Fit a random forest classifier and observe the accuracy.
Machine Learning Case Study 4: Principal component analysis using scikit learn.
Load the digits dataset from sklearn and write a helper function to plot the image. Fit a logistic regression model and observe the accuracy. Using scikit learn perform a PCA transformation such that the transformed dataset can explain 95% of the variance in the original dataset. Compare it with a model and also comment on the accuracy. Compute the confusion matrix and count the number of instances that has gone wrong. For each of the wrong sample, plot the digit along with predicted and original label.
Machine Learning Training Case Study 5: Read the datafile “letterCG.data” and set all the numerical attributes as features. Split the data in to train and test sets.
Fit a sequence of AdaBoostClassifier with varying number of weak learners ranging from 1 to 16, keeping the max_depth as 1. Plot the accuracy on test set against the number of weak learners, using decision tree classifier as the base classifier.
Industry: Social Media Problem Statement: You as ML expert have to do analysis and modeling to predict the number of shares of an article given the input parameters.
Actions to be performed: Load the corresponding dataset. Perform data wrangling, visualization of the data and detect the outliers, if any. Use the plotly library in Python to draw useful insights out of data. Perform regression modeling on the dataset as well as decision tree regressor to achieve your goal. Also, use scaling processes, PCA along with boosting techniques to optimize your model to the fullest.
Machine Learning Certification Project #2:
Industry: FMCG Problem Statement: You as an ML expert have to cluster the countries based on various sales data provided to you across years.
Actions to be performed: You have to apply an unsupervised learning technique like K means or Hierarchical clustering so as to get the final solution. But before that, you have to bring the exports (in tons) of all countries down to the same scale across years. Plus, as this solution needs to be repeatable you will have to do PCA so as to get the principal components which explain the max variance.
The average Payscale of a Machine Learning Engineer in Melbourne, Australia, is $529.
The average Payscale of a Machine Learning Engineer in Melbourne is $143,482 per year.
Some of the top job roles in the field of Machine Learning in Melbourne are
Machine Learning Engineer
Computer Vision Engineer
Edureka’s best Machine Learning course gives you all the necessary skills to become eligible for such roles.
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