Classification, Clustering, and Information Retrieval through a series of practical case studies. You will learn the necessary skills for using the machine learning techniques to solve complex real-world problems, by identifying the right method for your task and implementing the right algorithm successf...
Linear regression, logistic regression, K-means, random forest algorithm, SVM algorithm, decision tree, KNN algorithm, Naive Bayes algorithm, gradient and AdaBoost algorithm, dimensionality reduction algorithms. Why do companies hire Machine Learning Engineers? Machine learning engineers use ML to improve...
AlgorithmAttritionCustomerMachine LearningPredictionCustomers are so important in business that every firm should put great effort into retaining them. To achieve that with some measure of success, the firm needs to be able to predict the behaviour of their customers with respect to churn or ...
Dataset is an integral part of machine learning applications. It can be available in different formats like .txt, .csv, and many more. In supervised machine learning, the labeled training dataset is used, and in unsupervised, no label is needed. If you are a beginner, we recommend you to ...
(for example, kernel parameters, activation functions, as well as the choice and settings of the training algorithm). Three datasets are involved in model construction and selection. A training set is used as an optimization target for models to learn from for a given choice of hyperparameters....
Moreover, the advent and proliferation of machine learning and artificial intelligence technologies have dramatically amplified the demand for sophisticated algorithms and, by extension, the professionals adept at developing them. Consequently, the job market for algorithm developers has become fiercely ...
The entire model is created in a Jupyter Notebook, and you are required to embed it into the company’s website. The system you build should be able to redirect customers to different touchpoints on the website based on their actions. For instance, if the machine learning algorithm ...
The course is created on the theory that Games are the simplest test environment for AI, and when an algorithm can beat a game, it is proof that same principles can be applied to real world challenges. Therefore, the course uses a simulated AI environment, OpenAI Gym (a project backed by...
in-depth learning became essential for machine learning practitioners and even for many software engineers. This book provides a wide range of role for data scientists and software engineers with experience in machine learning. You will start with the basics of deep learning and quickly move on to...
If you want to learn more about logistic regression and also for other classification algorithms, here is theOverview of Machine Learning Algorithms: Classification. KNeighboursClassifier This algorithm can work well with sparse data since it computes distances between data points and can handle high-...