English | Size: 4.71 GB
Genre: eLearning
What you’ll learn
The course provides path to start career in Data Science , Artificial Intelligence, Machine Learning
Problem Solving Approach
Impress interviewers by showing an understanding of the Machine Learning Algorithm concept
Python Basic to Advance Concept with Numpy, Pandas, Matplotlib, Seaborn, Plotly Library
Scikit Learn Library in Depth
Machine Learning Algorithms such as Linear, Logistic, SVM, KNN, K Mean, Naïve Bayes, Decision Tree and Random Forest
Machine Learning Types Such as Supervise Learning, Unsupervised Learning, Reinforcement Learning
Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation
This Course will design to understand Machine Learning Algorithms with case Studies using Scikit Learn Library. The Machine Learning Algorithms such as Linear Regression, Logistic Regression, SVM, K Mean, KNN, Naïve Bayes, Decision Tree and Random Forest are covered with case studies using Scikit Learn library. The course provides path to start career in Data Science , Artificial Intelligence, Machine Learning. Machine Learning Types such as Supervise Learning, Unsupervised Learning, Reinforcement Learning are also covered. Machine Learning concept such as Train Test Split, Machine Learning Models, Model Evaluation are also covered.
Who this course is for:
The course is ideal for beginners, as it starts from the fundamentals and gradually builds up your skills in Machine Learning Algorithms
People interested to learn Machine Learning Algorithms using Scikit Learning Library and Python
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