Let’s transform data into information and information into insight
Machine learning is one of the most popular data science methodologies. Machine learning differs from other computer-assisted decision-making processes in that it uses data to create prediction algorithms. Some of the most popular machine learning products you will come across in this course include building Chatbot, speech recognition, movie recommendation systems, and spam detectors. This course will teach you popular machine learning algorithms, starting from the basics of python programming to data visualization, Understanding machine learning with Deployment of ML models, principal component analysis, and regularization by building a movie recommendation system. You will learn about training data, and how to use a data set to discover potentially predictive relationships.
What you'll learn
- Use Python for Data Science and Machine Learning
- Use Spark for Big Data Analysis
- Implement Machine Learning Algorithms
- Learn to use NumPy for Numerical Data
- Learn to use Pandas for Data Analysis
- Learn to use Matplotlib for Python Plotting
- Learn to use Seaborn for statistical plots
- Use Plotly for interactive dynamic visualizations
- Use SciKit-Learn for Machine Learning Tasks
- K-Means Clustering
- Logistic Regression
- Linear Regression
- Random Forest and Decision Trees
- Natural Language Processing and Spam Filters
- Neural Networks
- Support Vector Machines
Requirements
- Desktop/ Laptop
- Internet connectivity min 2 Mbps
Target Audience
- Data scientist
- Software Developer
- Machine learning
- Data analytics
