Machine Learning Training

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New Batches Starts For Machine Learning Training From November

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Machine Learning Training

This course will nurture and transform you into a highly-skilled professional with an in-depth knowledge of various algorithms and techniques, such as regression, classification, supervised and unsupervised learning, Natural Language Processing, etc

Invictus Engineers’ ML training also equips you with Python programming language, a core to predicting things from data

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Weeks Duration

Hr/Week Therory

Hr/Week Lab

Students Per Batch

1. Introduction to Machine Learning & Scikit-Learn

Introduction

ML Applications
Choosing the Right ML Algorithm for the requirement

Scikit-Learn package

Pros of Scikit-Learn
Cons of Scikit-Learn
Comparing it with other Frameworks

Data Representation for Scikit-Learn

Tables of Data
Features Matrix and Target Matrix

Data Preprocessing

Untidy (Messy) Data
1. Handling Missing Values
2. Dealing with Outliers
Dealing with Categorical Features (Nominal & Ordinal)
Feature Engineering
Rescaling Data

Scikit-Learn API

Its working
1. Estimator
2. Predictor
3. Transformer

Supervised & Unsupervised Learning

Supervised Learning
Unsupervised Learning
Reinforcement Learning

2. Unsupervised Learning – Applications

Introduction

Clustering

Types of Clustering
Applications of Clustering in different fields

Exploring a Dataset – Wholesale Customers Dataset (Sample data)

Steps for Understanding the Dataset

Data Visualization

Loading the Dataset
Visualization Tools
k-means Algorithm
Deeper look into k-means Algorithm
1. Initialization Method
2. Setting the Number of Clusters

Mean-Shift Algorithm

Deeper look into Mean-Shift Algorithm

DBSCAN Algorithm

Deeper look into DBSCAN Algorithm

Evaluating the Performance of Clusters

Available Metrics for Evaluating in Scikit-Learn

3. Introduction to Supervised Learning

Introduction

Model Validation and Testing

Data Partitioning: Dividing data into subsets
Clarifying the Split Ratio
Cross-Validation

Evaluation Metrics: Performance Evaluation

Evaluation Metrics for Classification Tasks
1. Confusion Matrix
2. Accuracy
3. Precision
4. Recall
Choosing an Evaluation Metric for the purpose of study
Evaluation Metrics for Regression Tasks

Error Analysis

Bias, Variance, and Data Mismatch

4. Supervised Learning Algorithms

Introduction

Exploring the Dataset

Understanding the Dataset

The Naive Bayes Algorithm

How Naive Bayes Algorithm Work?

The Decision Tree Algorithm

How Decision Tree Algorithm Work?

The Support Vector Machine Algorithm

How SVM Algorithm Work?

Error Analysis

Accuracy, Precision, and Recall

5. Supervised Learning – Neural Networks

Introduction

Artificial Neural Networks

How Do ANNs Work?
1. Forward Propagation
2. Cost Function
3. Backpropagation
4. Updating the Weights and Biases
Understanding the Hyperparameters
1. Number of Hidden Layers and Units
2. Activation Functions
3. Regularization
4. Batch Size
5. Learning Rate
6. Number of Iterations
Applications of Neural Networks
Limitations of Neural Networks

Applying an Artificial Neural Network

Scikit-Learn’s Multilayer Perceptron

Performance Analysis

Error Analysis
Hyperparameter Fine-Tuning
Model Comparison

6. Building a Machine Learning Application

Introduction

Program Definition

Building a Program – Key Stages
1. Preparation
2. Creation
3. Interaction
Understanding the Dataset

Saving and Loading a Trained Model

Saving a Model
Loading a Model

Testimonial's

Deepak K

I have undergone training in a machine learning course from Invictus. The course was really helpful and the faculty was good and friendly. Placement assistance was also good. Thank you so much for giving me this opportunity, have a bright future.

Pradeep Y

I would like to extend a thank you to Invictus for providing an excellent machine learning training course. The wealth of knowledge imparted by the trainer has been invaluable and has given me a strong understanding of the subject matter. Thank you again, Invictus.

Abhinav.M

I have joined the Machine Learning Training course at Invictus. I must say a great amount of knowledge has been delivered by the trainer, which helped me to gain a strong knowledge of the subject. Thank You Invictus.

T. Akshay

I have completed the Machine Learning Training course at Invictus. I would like to express my gratitude to the trainer for their knowledge and expertise which has helped me gain a strong understanding of the subject matter. Thank you, Invictus.

A. Akhilesh

This was a very good hands-on machine learning experience. The training sessions and detailed course curriculum were both helpful. The trainer did a great job of covering each and every topic with care.

Machine Learning Training

Announcement

Enroll Now For Free Demo

Machine Learning Training

Share This Course

1. Introduction to Machine Learning & Scikit-Learn

2. Unsupervised Learning – Applications

Introduction

3. Introduction to Supervised Learning

Introduction

4. Supervised Learning Algorithms

Introduction

5. Supervised Learning – Neural Networks

Introduction

6. Building a Machine Learning Application

Introduction

Testimonial's

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