Name: Practical Machine Learning with TensorFlow 2.0 and Scikit
Brand: Acme Collins School
Price: 3000.00 INR
Availability: InStock
Rating: 0 (24 reviews)

Govt. Verified Certification
Job Credibility
Certification Valid for Life
Lifetime Access To E-learning
On-demand video
Flexible Learning
Certificate of Completion

Mode of Exam : Online
Duration : 1 Hour
Multiple Choice Questions are asked
No. of Questions are asked : 50
Passing Marks : 25 (50%)
There is no negative marking

Total: 55 lectures

Overview of the Anaconda Distribution
Installing the Anaconda Distribution for Scikit-Learn
Installing TensorFlow 2.0 from the Anaconda Distribution
Install Scikit-Learn and Tensorflow 2.0 Manually Through pip

What Is Machine Learning?
First Scikit-Learn Model
Overfitting and Regularization
Probability and Statistics Review
Probability Distribution and Metrics

Supervised Learning and KNN
Logistic Regression
Naïve Bayes
Support Vector Machines
Decision Trees
Ensemble Methods

K-means and Hierarchical Clustering
Connectivity and Density Clustering
Gaussian Mixture Models
Variational Bayesian Gaussian Mixture Models
Decomposing Signals into Components
Signal Decomposition with Factor and Independent Component Analysis
Novelty Detection
Outlier Detection
Locally Linear Embedded Manifolds
Multi-Dimensional Scaling and t-SNE Manifolds
Density Estimation
Restricted Boltzmann Machine

TensorFlow 2.0 Overview
TensorFlow 2.0's Gradient Tape
Working with Neural Networks and Keras
Keras Customization
Custom Networks in Keras
Core Neural Network Concepts
Regression and Transfer Learning
TensorFlow Estimators and TensorBoard

Introduction to ConvNets
ConvNets In Keras
Image Classification with Data Augmentation
Convolutional Autoencoders
Denoising and Variational Autoencoders
Custom Generative Adversarial Networks
Semantic Segmentation
Neural Style Transfer

Using Word Embeddings
Text Pipeline with Tokenization for Classification
Sequential Data with Recurrent Neural Networks
Best Practices with Recurrent Neural Networks
Time Series Forecasting
Forecasting with CNNs and RNNs

NLP Language Models
Generating Text from an LSTM
Sequence to Sequence Models
MT Seq2Seq with Attention
NLP Transformers
Training Transformers and NLP In Practice

Are you looking to take an online course in practical machine learning or machine learning with TensorFlow? If you want to get extensive information about machine learning with scikit-learn and TensorFlow. Then this course is an excellent resource that is designed for you only. When you enroll in this course, you learn various techniques to do efficient machine learning tasks. If you know about pandas and NumPy or an absolute beginner, this course also offers many advantages. This online practical machine learning course in TensorFlow 2.0 and Scikit contains up-to-date content. That prepares you for the upcoming and latest trend you need to face. You will know the theory and practical knowledge. By the end of the course, you will have comprehensive information with many real-life examples to explain to the user.

What will you get when you take our practical ML with Tensorflow 2.0 and Scikit course?

Enhancing present ML skills with fundamentals of practical machine learning with Scikit and Tensorflow.
Get practical and comprehensive information about each concept and also learn supervised and unsupervised ML with scikit.
Understand neural networks with Tensorflow 2.0 and, aside from this, gain expertise in reinforcement learning.
This course also helps you to know about deep learning and image classification with time series.

Who can take this machine learning with the scikit and TensorFlow 2.0 course?

If you are a developer and familiar with pandas and NumPy and want to learn ML terminologies. Also, any interested candidate who wants to get a highly demanding skill with a government-approved certificate.

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Yes. It is Completely Online. We don't provide offline classes for any of our courses.

Yes, it is government Certified. Acme Collins School is authentic and approved, which makes it the right choice for anyone who wants to procure a certificate of importance Read More.

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What will you get when you take our practical ML with Tensorflow 2.0 and Scikit course?

Who can take this machine learning with the scikit and TensorFlow 2.0 course?

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