KEY FEATURES
Build, Train, and Optimize Various Deep Learning Models Using TensorFlow and Keras
The Deep Learning Course is designed to provide you with a comprehensive understanding of deep learning. Throughout this course, you will delve into various deep-learning models, and learn about neural network topologies. You will gain hands-on experience with TensorFlow and its different data types, and learn how to use frameworks such as Keras for building and training models. The course covers essential deep learning concepts including convolutional and recurrent neural networks, autoencoders, and data augmentation techniques, culminating in a hands-on project to solidify your learning.
This course covers crucial topics, including the principles and applications of deep learning, the structure and functioning of neural networks, and practical implementation using TensorFlow and Keras. You will also learn how to work with datasets such as MNIST and apply advanced techniques like data augmentation to enhance model performance.
What you’ll learn
- Access 18 lectures & 16 hours of content 24/7
- Understand the basics of TensorFlow & its significance in the deep learning landscape
- Understand the various frameworks available for deep learning & their unique features
- Delve into the structure & functioning of neural networks, including activation functions and optimization techniques
- Implement data augmentation techniques to improve model robustness & performance
- Apply the knowledge gained throughout the course to a comprehensive hands-on project, showcasing your skills in deep learning
Who this course is for
- Anyone interested in artificial intelligence
- Aspiring AI engineers
- Data scientists & professional developers
PRODUCT SPECS
Important Details
- Length of time users can access this course: lifetime
- Access options: desktop & mobile
- Redemption deadline: redeem your code within 30 days of purchase
- Experience level required: all levels
- Certificate of Completion ONLY
- Updates included
- Closed captioning NOT available
- NOT downloadable for offline viewing
- Have questions on how digital purchases work? Learn more here
Requirements
- Basic understanding of Python programming, including familiarity with libraries such as NumPy and Pandas
- Essential knowledge of linear algebra, calculus, and probability/statistics
- Basic understanding of data structures and control flow
THE EXPERT
GreyCampus | EdTech Platform
GreyCampus helps people power their careers through skills and certifications. They strongly advocate for continuous upskilling and the acquisition of certifications as crucial to maintaining long-term success in one’s career. As older skills rapidly lose relevance, the demand for newer, sought-after skills is rapidly increasing. GreyCampus firmly believes that staying skilled will keep you ahead in your career.
KEY FEATURES
Apply Keras Effectively to Deep Learning Tasks
Welcome to “Keras for Deep Learning,” a comprehensive course designed to provide you with the essential knowledge and skills needed to harness the power of Keras for deep learning. Throughout this program, you will explore a wide range of deep learning concepts, algorithms, and practical applications, focusing on building, training, and deploying neural networks using the Keras framework.
This course covers crucial topics, including an introduction to Keras, testing different versions of Keras, and understanding the key differences between TensorFlow and Keras. You will also delve into various types of neural networks and their applications, gaining hands-on experience with Keras to build effective deep-learning models.
What you’ll learn
- Access 3 lectures & 3 hours of content 24/7
- Gain a solid understanding of the Keras framework, its features, and benefits
- Test & work with different versions of Keras to leverage its latest features and improvements
- Understand the key differences & integration between TensorFlow and Keras, and how to use them together effectively
- Explore various types of neural networks, including feedforward networks, convolutional neural networks (CNNs) & recurrent neural networks (RNNs), and understand their applications in different domains
Who this course is for
- This course is tailored for aspiring deep learning practitioners and AI enthusiasts. It aims to enhance your proficiency in applying Keras effectively to deep learning tasks.
PRODUCT SPECS
Important Details
- Length of time users can access this course: lifetime
- Access options: desktop & mobile
- Redemption deadline: redeem your code within 30 days of purchase
- Experience level required: all levels
- Certificate of Completion ONLY
- Updates included
- Closed captioning NOT available
- NOT downloadable for offline viewing
- Have questions on how digital purchases work? Learn more here
Requirements
- Basic understanding of Python programming including familiarity with libraries such as NumPy and Pandas
- Understanding of basic machine learning concepts and algorithms
- Basic knowledge of neural networks and deep learning concepts is beneficial but not required
THE EXPERT
GreyCampus | EdTech Platform
GreyCampus helps people power their careers through skills and certifications. They strongly advocate for continuous upskilling and the acquisition of certifications as crucial to maintaining long-term success in one’s career. As older skills rapidly lose relevance, the demand for newer, sought-after skills is rapidly increasing. GreyCampus firmly believes that staying skilled will keep you ahead in your career.
KEY FEATURES
Advanced Machine Learning Concepts, Algorithms, and Practical Applications
Welcome to “Advanced Machine Learning with Python,” a comprehensive course designed to equip you with the advanced knowledge and skills needed to excel in machine learning. Throughout this program, you will explore various advanced machine learning concepts, algorithms, and practical applications.
This course covers crucial topics, including feature selection, data preprocessing, bagging and boosting techniques, and model tuning with grid search. You will also delve into specific algorithms such as linear regression, random forest, and Naive Bayes theorem, gaining hands-on experience with Python to build and optimize machine learning models.
What you’ll learn
- Access 9 lectures & 5.5 hours of content 24/7
- Gain a solid understanding of feature selection techniques to improve model performance by selecting the most relevant features
- Learn advanced data preprocessing methods, including handling missing values, scaling & normalization
- Explore ensemble learning techniques such as bagging & boosting to enhance model accuracy and robustness
- Understand the process of model tuning using grid search to find the optimal hyperparameters for your models
- Dive deep into linear regression, understanding its principles & applications
Who this course is for
- Data analysts and data scientists
- Anyone interested in data analysis
PRODUCT SPECS
Important Details
- Length of time users can access this course: lifetime
- Access options: desktop & mobile
- Redemption deadline: redeem your code within 30 days of purchase
- Experience level required: basic to intermediate
- Certificate of Completion ONLY
- Updates included
- Closed captioning NOT available
- NOT downloadable for offline viewing
- Have questions on how digital purchases work? Learn more here
Requirements
- Basic understanding of Python Programming including familiarity with libraries such as NumPy, Pandas, and Scikit-learn
- Understanding of basic machine learning concepts and algorithms
- Basic knowledge of statistics and probability is beneficial
THE EXPERT
GreyCampus | EdTech Platform
GreyCampus helps people power their careers through skills and certifications. They strongly advocate for continuous upskilling and the acquisition of certifications as crucial to maintaining long-term success in one’s career. As older skills rapidly lose relevance, the demand for newer, sought-after skills is rapidly increasing. GreyCampus firmly believes that staying skilled will keep you ahead in your career.
KEY FEATURES
Utilize TensorFlow for Deep Learning Applications
Deep Learning with TensorFlow is designed to equip you with the essential knowledge and skills to master deep learning techniques using TensorFlow. This comprehensive program covers the fundamentals of TensorFlow, from installation to hands-on projects, ensuring you gain practical experience in building and deploying deep learning models. You will learn the basics of TensorFlow, understand its installation process, and work on a mini project that consolidates your learning by applying TensorFlow to solve a real-world problem.
What you’ll learn
- Access 4 lectures & 1.5 hours of content 24/7
- Gain a solid understanding of what TensorFlow is, its significance & its role in the deep learning ecosystem
- Install TensorFlow on various platforms, including configuring the environment & troubleshooting common issues
- Implement foundational algorithms, build & optimize models
- Utilize TensorFlow to extract meaningful insights from data
- Apply your knowledge in a hands-on mini project, where you will build and train a simple deep learning model using TensorFlow, reinforcing your understanding of the framework
Who this course is for
- Anyone interested in artificial intelligence
- Aspiring AI engineers
- Data scientists & professional developers
PRODUCT SPECS
Important Details
- Length of time users can access this course: lifetime
- Access options: desktop & mobile
- Redemption deadline: redeem your code within 30 days of purchase
- Experience level required: all levels
- Certificate of Completion ONLY
- Updates included
- Closed captioning NOT available
- NOT downloadable for offline viewing
- Have questions on how digital purchases work? Learn more here
Requirements
- Basic understanding of Python programming, including familiarity with libraries such as NumPy and Pandas
- Essential knowledge of linear algebra, calculus, and probability/statistics
- Basic understanding of data structures and control flow
THE EXPERT
GreyCampus | EdTech Platform
GreyCampus helps people power their careers through skills and certifications. They strongly advocate for continuous upskilling and the acquisition of certifications as crucial to maintaining long-term success in one’s career. As older skills rapidly lose relevance, the demand for newer, sought-after skills is rapidly increasing. GreyCampus firmly believes that staying skilled will keep you ahead in your career.
KEY FEATURES
Utilize Keras and TensorFlow to Extract Meaningful Insights from Data
Deep Learning With Keras & TensorFlow is a comprehensive course designed to equip you with the essential knowledge and skills needed to master deep learning using the powerful Keras and TensorFlow frameworks. Throughout this program, you will explore many deep learning concepts, and algorithms, focusing on building, training, and deploying deep neural networks.
This course covers crucial topics, including an introduction to TensorFlow, hands-on experience with TensorFlow 2.0, and a mini-project explanation to solidify your understanding. You will also delve into Keras, learning about its installation, various network types, and how to leverage its simplicity for rapid prototyping and experimentation. By the end of this course, you will be proficient in building complex models to tackle real-world problems.
What you’ll learn
- Access 6 lectures & 3.5 hours of content 24/7
- Gain a solid understanding of TensorFlow’s architecture &core components
- Explore the new features & improvements in TensorFlow 2.0, including eager execution and the Keras API
- Install & set up Keras and understand its integration with TensorFlow.
- Discover the simplicity & efficiency of Keras for building deep learning models.
- Explore various types of neural networks, including feedforward networks, convolutional neural networks (CNNs) & recurrent neural networks (RNNs)
Who this course is for
- This course is tailored for aspiring deep learning practitioners and AI enthusiasts
PRODUCT SPECS
Important Details
- Length of time users can access this course: lifetime
- Access options: desktop & mobile
- Redemption deadline: redeem your code within 30 days of purchase
- Experience level required: all levels
- Certificate of Completion ONLY
- Updates included
- Closed captioning NOT available
- NOT downloadable for offline viewing
- Have questions on how digital purchases work? Learn more here
Requirements
- Basic understanding of Python programming including familiarity with libraries such as NumPy and Pandas
- Understanding of basic machine learning concepts and algorithms
- Basic knowledge of neural networks and deep learning concepts is beneficial but not required
THE EXPERT
GreyCampus | EdTech Platform
GreyCampus helps people power their careers through skills and certifications. They strongly advocate for continuous upskilling and the acquisition of certifications as crucial to maintaining long-term success in one’s career. As older skills rapidly lose relevance, the demand for newer, sought-after skills is rapidly increasing. GreyCampus firmly believes that staying skilled will keep you ahead in your career.
KEY FEATURES
Apply PySpark Techniques Effectively to Extract Insights from Large Datasets
PySpark for Data Scientists is a comprehensive course designed to provide you with the essential knowledge and skills needed to harness the power of PySpark for big data analytics. Throughout this program, you will explore a wide range of concepts, algorithms, and practical applications, focusing on the core principles of distributed data processing and large-scale data analysis.
This course covers crucial topics, including the skills required for data science and understanding PySpark and its applications. You will delve into data manipulation techniques, gain hands-on experience with data handling and transformation, and implement various PySpark functionalities.
What you’ll learn
- Access 14 lectures & 4.5 hours of content 24/7
- Gain a solid understanding of fundamental PySpark concepts & principles
- Explore key data manipulation techniques such as data frames, RDDs & SQL queries in PySpark
- Learn techniques for distributed data processing & optimization
- Understand & implement strategies for data cleaning and transformation
Who this course is for
- Tailored for aspiring data scientists and data engineering enthusiasts
PRODUCT SPECS
Important Details
- Length of time users can access this course: lifetime
- Access options: desktop & mobile
- Redemption deadline: redeem your code within 30 days of purchase
- Experience level required: all levels
- Certificate of Completion ONLY
- Updates included
- Closed captioning NOT available
- NOT downloadable for offline viewing
- Have questions on how digital purchases work? Learn more here
Requirements
- Basic understanding of Python programming including familiarity with libraries such as NumPy and Pandas
- Understanding of data manipulation, exploratory data analysis, and basic machine learning concepts
- Basic knowledge of big data concepts and distributed computing is beneficial but not required
THE EXPERT
GreyCampus | EdTech Platform
GreyCampus helps people power their careers through skills and certifications. They strongly advocate for continuous upskilling and the acquisition of certifications as crucial to maintaining long-term success in one’s career. As older skills rapidly lose relevance, the demand for newer, sought-after skills is rapidly increasing. GreyCampus firmly believes that staying skilled will keep you ahead in your career.
KEY FEATURES
Sophisticated Data Visualizations and Advanced Data Analysis with Power BI
The Power BI Advanced Course is designed to gain mastery over advanced Power BI features and techniques, including creating sophisticated visualizations such as key influencers, waterfall charts, and decomposition trees. Learn to implement both static and dynamic row-level security to control data access. The course will cover advanced DAX functions for complex calculations, as well as advanced Power Query techniques for data transformation. Additionally, explore the integration of Power BI with other Microsoft services like MS Teams and PowerPoint, and learn to configure subscriptions and paginated reports. A comprehensive end-to-end project will consolidate your learning. This course will equip you with the skills and knowledge to utilize Power BI’s advanced features effectively and integrate machine learning concepts into your data analysis workflows.
What you’ll learn
- Access 24 lectures & 7.5 hours of content 24/7
- Master advanced Power BI features & visualization techniques
- Implement dynamic & static row-level security
- Utilize advanced DAX functions for complex calculations
- Integrate Power BI with other Microsoft services
- Gain hands-on experience with machine learning concepts & their application in Power BI
Who this course is for
- Power BI users seeking advanced skills
- Anyone interested in data visualization & reporting
PRODUCT SPECS
Important Details
- Length of time users can access this course: lifetime
- Access options: desktop & mobile
- Redemption deadline: redeem your code within 30 days of purchase
- Experience level required: basic to intermediate
- Certificate of Completion ONLY
- Updates included
- Closed captioning NOT available
- NOT downloadable for offline viewing
- Have questions on how digital purchases work? Learn more here
Requirements
- Basic to intermediate understanding of Power BI
- Essential knowledge of linear algebra, calculus, and probability/statistics
- Basic understanding of data structures and control flow
THE EXPERT
GreyCampus | EdTech Platform
GreyCampus helps people power their careers through skills and certifications. They strongly advocate for continuous upskilling and the acquisition of certifications as crucial to maintaining long-term success in one’s career. As older skills rapidly lose relevance, the demand for newer, sought-after skills is rapidly increasing. GreyCampus firmly believes that staying skilled will keep you ahead in your career.
KEY FEATURES
Tackle Complex Machine-Learning Challenges Using the R Programming Language
Machine Learning with R is designed to equip you with the essential knowledge and skills to master machine learning techniques using the R programming language. Throughout this comprehensive program, you will explore a wide range of machine learning concepts, algorithms, and practical applications, focusing on the core principles of predictive modeling and data analysis.
This course covers crucial topics, including the fundamentals of machine learning, linear and logistic regression, decision trees, random forests, K-Nearest Neighbors (KNN), Support Vector Machines (SVM), and evaluation metrics. Additionally, you will delve into time series analysis, gaining hands-on experience with data handling, model building, and implementing various algorithms using R. The course will also compare and contrast decision trees and random forests, providing you with a deep understanding of these popular techniques.
What you’ll learn
- Access 10 lectures & 10 hours of content 24/7
- Gain a solid understanding of fundamental machine learning concepts & principles
- Explore the SVM algorithm & its use in high-dimensional spaces for classification
- Compare & contrast decision trees and random forests, understanding their strengths and weaknesses
- Learn various metrics for evaluating machine learning models, including accuracy, precision, recall, F1 score & ROC-AUC
- Gain insights into time series data, understand trends, seasonality & noise, and apply models for forecasting
Who this course is for
- Data analysts and data scientists
- Anyone interested in data analysis
PRODUCT SPECS
Important Details
- Length of time users can access this course: lifetime
- Access options: desktop & mobile
- Redemption deadline: redeem your code within 30 days of purchase
- Experience level required: all levels
- Certificate of Completion ONLY
- Updates included
- Closed captioning NOT available
- NOT downloadable for offline viewing
- Have questions on how digital purchases work? Learn more here
Requirements
- Basic understanding of R programming, including familiarity with data manipulation and visualization libraries
- Essential knowledge of linear algebra, calculus, and probability/statistics
- Basic understanding of data structures and control flow in R
THE EXPERT
GreyCampus | EdTech Platform
GreyCampus helps people power their careers through skills and certifications. They strongly advocate for continuous upskilling and the acquisition of certifications as crucial to maintaining long-term success in one’s career. As older skills rapidly lose relevance, the demand for newer, sought-after skills is rapidly increasing. GreyCampus firmly believes that staying skilled will keep you ahead in your career.
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