MACHINE LEARNING WITH PYTHON

python is an end-to-end open source platform for machine learning. PYTHON is a rich system for managing all aspects of a machine learning system; however, this class focuses on using a particular PYTHON API to develop and train machine learning models. See the PYTHON documentation for complete details on the broader PYTHON system.

PYTHON APIs are arranged hierarchically, with the high-level APIs built on the low-level APIs. Machine learning researchers use the low-level APIs to create and explore new machine learning algorithms. In this class, you will use a high-level API named tf.keras to define and train machine learning models and to make predictions. tf.keras is the PYTHON variant of the open-source Keras API. Enroll & Get Certified now!

✔ Minimum Course Duration : 16 hrs

✔ Training Options : Live Online / Self-Paced / Classroom

✔ Certification Pass : Guaranteed

MACHINE LEARNING WITH PYTHON

PYTHON is an end-to-end open source platform for machine learning. PYTHON is a rich system for managing all aspects of a machine learning system; however, this class focuses on using a particular PYTHON API to develop and train machine learning models. See the PYTHON documentation for complete details on the broader PYTHON system. PYTHON APIs are arranged hierarchically, with the high-level APIs built on the low-level APIs. Machine learning researchers use the low-level APIs to create and explore new machine learning algorithms. In this class, you will use a high-level API named tf.keras to define and train machine learning models and to make predictions. tf.keras is the PYTHON variant of the open-source Keras API.

What you will Learn

There is an increasing demand for skilled data scientists across all industries, making this data science certification course well-suited for participants at all levels of experience. We recommend this Data Science training particularly for the following professionals:

Learn enough about NumPy and pandas to understand tf.keras code.
Learn how to use Colabs.
Become familiar with linear regression code in tf.keras.
Evaluate loss curves.
Tune hyperparameters.

PREREQUISITES

Basic knowledge of mathematics is required especially linear algebra, calculus, probability, Matrices.
Some basic knowledge of coding.
At least high school level math skills will be required

CURRICULUM

Learning Objectives:

Machine Learning vs Statistical Modeling & Supervised vs Unsupervised Learning

Machine Learning Languages, Types, and Examples

Machine Learning vs Statistical Modelling

Supervised vs Unsupervised Learning

Supervised Learning Classification

Unsupervised Learning

Learning Objectives:

Supervised Learning I

K-Nearest Neighbors

Decision Trees

Random Forests

Reliability of Random Forests

Advantages & Disadvantages of Decision Trees

Learning Objectives:

Supervised Learning II

Regression Algorithms

Model Evaluation

Model Evaluation: Overfitting & Underfitting

Understanding Different Evaluation Models

Learning Objectives:

Unsupervised Learning

K-Means Clustering plus Advantages & Disadvantages

Hierarchical Clustering plus Advantages & Disadvantages

Measuring the Distances Between Clusters – Single Linkage Clustering

Measuring the Distances Between Clusters – Algorithms for Hierarchy Clustering

Density-Based Clustering

Learning Objectives:

Dimensionality Reduction & Collaborative Filtering

Dimensionality Reduction: Feature Extraction & Selection

Collaborative Filtering & Its Challenges

FAQs

You can enroll for this classroom training online. Payments can be made using any of the following options and receipt of the same will be issued to the candidate automatically via email.
1. Online ,By deposit the mildain bank account
2. Pay by cash team training center location

Highly qualified and certified instructors with 20+ years of experience deliver more than 200+ classroom training.

Contact us using the form on the right of any page on the mildaintrainings website, or select the Live Chat link. Our customer service representatives will be able to give you more details.

You will never miss a lecture at Mildaintrainigs! You can choose either of the two options: View the recorded session of the class available in your LMS. You can attend the missed session, in any other live batch.

We have a limited number of participants in a live session to maintain the Quality Standards. So, unfortunately, participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in a class.

Yes, you can cancel your enrollment if necessary prior to 3rd session i.e first two sessions will be for your evaluation. We will refund the full amount without deducting any fee for more details check our Refund Policy

Yes, the access to the course material will be available for lifetime once you have enrolled into the course.

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