Machine Learning & Deep Learning in Python & R
Learn about Machine Learning, Neural Networks, CNN, time series analysis and much more using Python & R studio
What you’ll learn
- Learn how to solve a real-life problem using the Machine learning techniques
- Machine Learning models such as Linear Regression, Logistic Regression, KNN, etc.
- Advanced Machine Learning models such as Decision trees, XGBoost, Random Forest, SVM, etc.
- Understanding of basics of statistics and concepts of Machine Learning
- How to do basic statistical operations and run ML models in Python
- In-depth knowledge of data collection and data preprocessing for Machine Learning problem
- How to convert a business problem into a Machine learning problem
- Students will need to install Anaconda software but we have a separate lecture to guide you install the same
The course is created on the basis of three pillars of learning:
- Know (Study)
- Do (Practice)
- Review (Self-feedback)
We have created a set of concise and comprehensive videos to teach you all the Excel-related skills you will need in your professional career.
With each lecture, we have provided a practice sheet to complement the learning in the lecture video. These sheets are carefully designed to further clarify the concepts and help you with implementing the concepts on practical problems faced on-the-job.
Check if you have learned the concepts by comparing your solutions provided by us. Ask questions in the discussion board if you face any difficulty.
- People pursuing a career in data science
- Working Professionals beginning their Data journey
- Statisticians needing more practical experience