Machine Learning & Deep Learning : Python Practical Hands-on

About this course

Interested in the field of Machine Learning? Then this course is for you!

Designed & Crafted by AI Solution Expert with 15 + years of relevant and hands on experience into Training , Coaching and Development.

Complete Hands-on AI Model Development with Python. Course Contents are:

• Understand Machine Learning in depth and in simple process. Fundamentals of Machine Learning
• Understand the Deep Learning Neural Nets with Practical Examples.
• Understand Image Recognition and Auto Encoders.
• Machine learning project Life CycleSupervised & Unsupervised Learning

Data Pre-Processing

Algorithm Selection

Data Sampling and Cross Validation

Feature Engineering

Model Training and ValidationK -Nearest Neighbor AlgorithmK- Means Algorithm

Accuracy Determination

Visualization using Seaborn

You will be trained to develop various algorithms for supervised & unsupervised methods such as KNN , K-Means , Random Forest, XGBoost model development. Understanding the fundamentals and core concepts of machine learning model building process with validation and accuracy metric calculation. Determining the optimum model and algorithm. Cross validation and sampling methods would be understood. Data processing concepts with practical guidance and code examples provided through the course. Feature Engineering as critical machine learning process would be explained in easy to understand and yet effective manner.

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.

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