Machine Learning

Introduction to Machine Learning Course

ML for Everyone: Courses for Beginners, Professionals, and Innovato

What you'll learn

This course includes

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Course Content

Python basic Python concepts & terms Python fundamentals Python data structure & modules

What is machine learning? Applications of machine learning, Supervised vs Unsupervised Learning, Python libraires suitable for ML

Training& Testing, Cross validation, Features & labels, Pickling’s & Scaling, Techniques & Error metrics.

 

Linear regression & Forecasting, Prediction using regression, Logisitic regression & model evaluation, Support vector machines, K-N classification, K –means clustering, Random Forest linear

Content based recommender systems, Collaborative Filtering

Introduction to NLTK, BASICS & LAXICAL PROCESSING, Text Classification, stop words stemming lemmatization, named entity recognition, conduct sentiment analysis using Naïve bayes

Information & Training flow of neural network, Convolutional & Recurrent neural networks, Creating & Deploying networks using TensorFlow & karas

Implementation of all algorithms using sklern

Introduction to open Cv (Image processing) Learning basic image manipulations Introduction to CNN CNN Institution Convolution Operation pooling Flattering building a CNN using python Training the model

Requirements

Description

Machine learning is the study of computer algorithms that can better themselves automatically based on experience and data. It is a subfield of computer science and artificial intelligence (AI). Machine learning is changing the world; it is present in many important industries, including healthcare, education, transportation, food, and entertainment. With the aid of machine learning, almost every part of our daily lives will become easier and more efficient. Housing, cars, shopping, food ordering, and so on will all become easier and more efficient.

Tools Included

Pricing plans

Self Paced
0
Mentor Led
0

Certificate Included

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