Dive into the essentials of AI with our “Fundamentals of Machine Learning” course. This step-by-step guide is crafted to transition you from novice to machine learning expert, covering both foundational principles and advanced algorithms across 22 lectures.
You’ll develop a deep understanding of machine learning, readying you to make your impact in AI. Begin your journey now and master the future of technology.
Blast off into a new world of possibilities with our “Fundamentals to Machine Learning” course! It’s your launchpad to the limitless universe of Machine Learning and stepping stone to the world of AI.
Start with Machine Learning fundamentals, understanding both supervised and unsupervised models. Dive into evaluation metrics for regression, classification, and clustering, essential for assessing your models' performance.
Dive into the core of machine learning with the Bias-Variance trade-off and Overfitting. Grasp these essential concepts, critical for balancing model accuracy and generalizability.
Advance to overcoming Overfitting using Regularization. Learn key techniques like Ridge and Lasso Regression to fine-tune your models for optimal performance.
Explore Linear Regression, a foundational yet powerful model. Understand the Ordinary Least Squares (OLS) process, its assumptions, and validation methods, assessing their strengths and weaknesses.
Progress to Logistic Regression, dissecting odds, log-odds, and the Maximum Likelihood Estimation (MLE). Evaluate the benefits and limitations of this critical model.
Journey through Linear Discriminant Analysis (LDA), a go-to method for linearly separable classes. Delve into its theory, assumptions, and practical applications, comparing it to Logistic Regression.
We will explore the captivating world of KNN, an algorithm that operates on a principle that is simple yet effective. During this expedition, you'll get a grasp of how KNN works step-by-step, its applications in classification problems, and how to determine the right number of neighbors, "k". We will also weigh its pros and cons, preparing you to make an informed decision on when and where to use it.
Next, we dive deep into the world of Decision Trees. Understand its intricate definition, become proficient with the step-by-step algorithm, and gain hands-on experience in building your own trees. Master the art of Recursive Binary Splitting and get a firm grasp on evaluating models with Gini Index, Entropy, and RSS. Weigh up the pros and cons of Decision Trees, arming yourself with a balanced understanding.
Ensemble methods such as Bagging, Random Forests, and advanced Boosting models like AdaBoost, GBM, and XGBoost will be your next destinations. These methods will equip you with powerful algorithms to improve your models' performance. You will get a grasp of step-by-step guide behind these algorithms and they compare.
Next, your interstellar journey will take you to the Clustering galaxies, where you'll be introduced to K-Means, Hierarchical Clustering, and DBSCAN. Each galaxy will reveal novel methods to discover hidden patterns in unlabelled data. We will also weigh its pros and cons, as well as metrics to use and how to Elbow method for K-Means, preparing you to make an informed decision on when and where to use it.
To navigate the multiverse of features efficiently, you will learn about Dimensionality Reduction including various Feature Selection techniques, and the infamous Principal Component Analysis with Elbow Method, a necessary compass to guide your models through the high-dimensional data spaces.
Before heading back to earth, one of our final destinations include the lands of Resampling Techniques and Optimization Algorithms for hyper-parameter tuning. Here, you'll learn how to assess and enhance your model's performance using techniques such as various Cross-Validation techniques, and Bootstrapping, as well as all popular optimization models.
Your journey doesn’t end with the course completion!
This course is just your springboard into the exciting world of Machine Learning! Now it’s your turn to take the leap, explore and make waves.
Dive into our exclusive eBooks and real-world case studies for a deep dive into practical Machine Learning applications.
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