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Go to Course: https://www.udemy.com/course/applied-machine-learning-with-python/
If you're interested in diving into the exciting world of Machine Learning, this comprehensive course on Coursera is an excellent choice. Designed by two experienced Data Scientists, the course aims to demystify complex theories, algorithms, and coding libraries, making them accessible even for beginners. Course Overview: This course takes a step-by-step approach, starting with fundamental concepts like Data Preprocessing and progressing through more advanced topics such as Deep Learning, Reinforcement Learning, Natural Language Processing, and Dimensionality Reduction. Each part of the curriculum is structured to build your knowledge gradually, ensuring a solid understanding of each component. Key Features: - Practical Focus: The course is rich in exercises based on real-world examples, enabling you to apply what you learn immediately. This hands-on approach is perfect for building practical skills. - Coding Templates: You will receive downloadable Python and R code templates, which you can use in your own projects to accelerate your learning. - Up-to-Date Content: As of June 2020, the course includes the latest updates, with deep learning code in TensorFlow 2.0 and cutting-edge boosting models like XGBoost and CatBoost. - Extensive Topics: Covering everything from Regression, Classification, Clustering, to NLP, Deep Learning, and Model Optimization, the course offers a well-rounded introduction to Machine Learning. Review: This course stands out for its clear explanations, practical exercises, and comprehensive coverage of Machine Learning topics. It strikes a good balance between theory and practice, making it suitable for beginners and those looking to deepen their understanding. The inclusion of downloadable code templates also provides added value, allowing you to experiment and implement models with confidence. Recommendation: I highly recommend this course for anyone interested in starting or advancing their career in Machine Learning. Whether you're a student, a data enthusiast, or a professional aiming to expand your skills, this course offers valuable insights and practical experience. Its structured approach, combined with up-to-date content and plenty of hands-on exercises, makes it a worthwhile investment in your educational journey. In summary, this Coursera course is an excellent resource that equips you with the knowledge and skills needed to excel in the dynamic field of Machine Learning. Enroll today and begin your journey into this lucrative and rapidly evolving field!
Interested in the field of Machine Learning? Then this course is for you! This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way. We will walk you step-by-step into the World of Machine Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science. This course is fun and exciting, but at the same time, we dive deep into Machine Learning. It is structured the following way:Part 1 - Data PreprocessingPart 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest RegressionPart 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest ClassificationPart 4 - Clustering: K-Means, Hierarchical ClusteringPart 5 - Association Rule Learning: Apriori, EclatPart 6 - Reinforcement Learning: Upper Confidence Bound, Thompson SamplingPart 7 - Natural Language Processing: Bag-of-words model and algorithms for NLPPart 8 - Deep Learning: Artificial Neural Networks, Convolutional Neural NetworksPart 9 - Dimensionality Reduction: PCA, LDA, Kernel PCAPart 10 - Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoostMoreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.Important updates (June 2020):CODES ALL UP TO DATEDEEP LEARNING CODED IN TENSORFLOW 2.0TOP GRADIENT BOOSTING MODELS INCLUDING XGBOOST AND EVEN CATBOOST!