Form this Machine Learning with Python Online Training you will able to learn all the Concepts of R ProgrammiMachine Learning with Python course with real-time scenarios, live examples by real-time professionals
Machine Learning
using Python & R
By: Professor
Course Content
Machine Learning
using Python & R
- Various machine learning algorithms in Python
- Apply machine learning algorithms in Python
- How to select the right data
- Which are the best features to use
- Additional feature selection techniques
- A feature selection case study
- Preprocessing Introduction
- Preprocessing Scaling Techniques
- How to preprocess your data
- How to scale your data
- Feature Scaling Final Project
- Various phases of Data Cleaning
- Functions used in Inspection
- Data Cleaning Techniques
- Uses of functions involved
- Use-cases for Data Cleaning using R
- Highly efficient machine learning algorithms
- Bagging Decision Trees
- The power of ensembles
- Random Forest Ensemble technique
- Boosting – Adaboost
- Boosting ensemble stochastic gradient boosting
- A final ensemble technique
- Introduction Model Tuning
- Parameter Tuning GridSearchCV
- A second method to tune your algorithm
- How to automate machine learning
- Which ML algo should you choose
- How to compare machine learning algorithms in practice
- Neural Networks introduction
- What is deep learning
- What is one hot encoding
- How to implement one hot encoding
- How to handle missing values
- How to impute missing values
- Introducing the MNIST dataset
- Programming a neural network in tensorflow
- Programming a neural network – multilayer perceptron in tensorflow
- Introduction to keras – a convient way to code neural networks
- What is a convolutional neural network
- How does a cnn work
- Creating a convolutional neural network from scratch
- What are RNNs – Introduction to RNNs
- Recurrent Neural Networks rnn in python
- LSTMs for beginners – understanding LSTMs
- long short term memory neural networks lstm in python
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