Machine Learning Program
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.
This is an all-inclusive program that will introduce you to the Python development language and expose you to the essentials of object-oriented programming. Python has surpassed Java as the top language used to introduce U.S. students to programming and computer science. This course will give you hands-on development experience and prepare you for a career as a professional Python programmer.
- Creating Your First Program in Python
- Data Types: Classifying Data in Python
- Implementing Input and Output Operations
- Operators: Performing Logical and Mathematical Operations
- Statements: Controlling the Flow of Program
- Strings: A Sequence of Characters
- Arrays: Arranging Similar Objects Systematically
- Implementing Functions in Python
- Lists and Tuples: Managing Data Systematically
- Dictionaries and Other Data Structures
- Recursion and Algorithms in Python
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.
- Data Preprocessing
- Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
- Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
- Clustering: K-Means, Hierarchical Clustering
- Association Rule Learning: Apriori, Eclat
- Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
- Natural Language Processing: Bag-of-words model and algorithms for NLP
- Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
- Dimensionality Reduction: PCA, LDA, Kernel PCA
- Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost
Expand your knowledge
Weekly Seminars with Industry Experts, Mock Interviews & Resume Building.
Only at Network Nuts.