296 Vector courses in London delivered On Demand

Course Overview Moho Studio is a vector-based 2D animation application ideal for creating games, tv shows, and web series. The Animation Skill using Moho Studio course is a step-by-step training program for aspiring animators and game designers. It will teach you how to master Moho Studio to create an animated keyboard-controlled walking character from scratch, as well as bring your character to life through different tools and features.  To set you up, you will first learn how to sketch and prepare your character, and then will gradually be introduced to different tools. By the end of the course, you will be able to create an animation action scene and add dynamism to your characters. You will have real-world skills that can be applied to a wide range of creative industries. This best selling Animation Skill using Moho Studio has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth Animation Skill using Moho Studio is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The Animation Skill using Moho Studio is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The Animation Skill using Moho Studio is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the Animation Skill using Moho Studio, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the Animation Skill using Moho Studio will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the Animation Skill using Moho Studio to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

Description Do you want to master the world's best photo editing software? Or are you new to Adobe Photoshop CC? Then enrol the Adobe Photoshop CC Foundation course and begin your acquaintance with the course. The course is for the learners who have little or no knowledge about the photo editor. You will start your journey from the beginning. You will be familiar with the user interface and know how to open and create an image in Adobe Photoshop. The course introduces you to the essential tools, brushes and other features so that you can able to decide which tools to select while editing. Additionally, the course illustrates the concepts of colour schemes and guides you on how to use the colors efficiently. The procedures of adding text and text styles, working with Layers, adjusting Layers, customizing the workspace, moving and transforming Pixels, cropping images, etc. will be covered in the course. Finally, the course shows you how to print, convert and export files from Photoshop. Shortly, the course gives you a general understanding of the application so that you can proceed with the advanced skills. Assessment: This course does not involve any MCQ test. Students need to answer assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Once the answers are submitted, the instructor will check and assess the work. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? Photoshop CC Masterclass - Beginner to Advanced is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our Photoshop CC Masterclass - Beginner to Advanced is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Adobe Photoshop CC Beginner Introduction Introduction FREE 00:03:00 Introduction to Photoshop Introduction to Photoshop 00:05:00 Understanding Types of Documents 00:04:00 Understanding Resolution 00:04:00 Creating New Documents 00:06:00 Using Artboards 00:05:00 Using CC Templates 00:03:00 Utilizing the Search Feature 00:02:00 Customizing the Workspace Using Workspace Presets 00:02:00 Moving, Closing, and Opening Panels 00:06:00 Understanding Document Views 00:06:00 Using the History Panel 00:06:00 Working with Layers Why Layers 00:02:00 Using Layers 00:07:00 Creating Fill Layers 00:05:00 Applying Blending Modes 00:04:00 Using Layer Styles 00:09:00 Discovering the Properties Panel 00:08:00 Understanding Selections Creating Basic Selections 00:09:00 Using the Lasso Tools 00:08:00 Understanding the Quick Select Tools 00:07:00 Editing the Quick Mask 00:04:00 Saving Selectionsv 00:04:00 Moving Selections to Layers.mp 00:03:00 Understanding and Using Color Understanding Color Modes 00:10:00 Creating Swatches 00:06:00 Using Masks and Advanced Layers Applying Layer Masks 00:00:00 Deleting Layer Masks 00:01:00 Organizing Layers 00:03:00 Merging Layers 00:02:00 Flattening Layers 00:02:00 Working with Layer Comps 00:06:00 Using Adjustment Layers Using Image Adjustments 00:07:00 Understanding Adjustment Layers 00:10:00 Using Layer Masks with Adjustment Layers 00:03:00 Cropping Images Using the Crop Tool 00:05:00 Using the Crop Tool to Add Canvas 00:02:00 Moving and Transforming Pixels Using Free Transform 00:04:00 Working with Other Transform Options 00:03:00 Flipping Pixels 00:01:00 Adding Text and Text Styles Using the Type Tool 00:10:00 Discovering Typesetting 00:08:00 Formatting Text 00:09:00 Creating Type on a Path 00:03:00 Warping Type 00:03:00 Using Styles on Type 00:08:00 Applying Special Effects Using Layer Styles 00:05:00 Working with Patterns 00:03:00 Applying Filters 00:04:00 Creating Pixels with Filters 00:06:00 Exporting from Photoshop Printing in Photoshop 00:03:00 Converting to CMYK 00:04:00 Converting to Other File Types 00:13:00 Using File Info 00:09:00 Conclusion Course Recap 00:03:00 Adobe Photoshop CC Intermediate Start Here Introduction FREE 00:03:00 Painting and Using Brushes Painting with Brushes 00:09:00 Using the Brushes Panel 00:06:00 Defining Custom Brushes 00:04:00 Saving Tool Presets 00:02:00 Using the History Brush 00:03:00 Using Vector Tools Working with Vector Shapes 00:10:00 Creating Custom Shapes 00:02:00 Using the Pen Tool 00:07:00 Discovering Paths 00:04:00 Understanding Vector Masks 00:03:00 Using Vector Objects and Spot Colors 00:06:00 Using Libraries What is the CC Library 00:02:00 Adding and Deleting Assets in the Library 00:03:00 Sharing Assets 00:02:00 Creating New Libraries 00:03:00 Sharing a Library 00:02:00 Advanced Special Effects Using the Blur Filters 00:06:00 Applying the Distort Filters 00:03:00 Creating a Pixelated Look 00:02:00 Stylizing Effects 00:02:00 Using Liquify 00:05:00 Using Smart Filters 00:04:00 Working with Smart Objects 00:03:00 Loading a Texture into Type 00:04:00 Working with RAW Images What is a Raw Image 00:05:00 Processing Raw Images 00:12:00 Opening a JPEG File in Raw 00:06:00 Retouching Basics Developing a Strategy for Retouching 00:04:00 Using Retouching Tools 00:10:00 Using the Dust and Scratches Filter 00:04:00 Applying Sharpening 00:08:00 Working with Face Aware Liquify 00:06:00 Automating Tasks Using Actions 00:03:00 Creating Actions 00:07:00 Using Droplets 00:05:00 Using the Image Processor 00:05:00 Creating an HDR Image 00:07:00 Creating a Panoramic Image 00:07:00 Integration with other Adobe Software Using PSD Files in InDesign 00:04:00 Using PSD Files in Illustrator 00:03:00 Using PSD Files in Dreamweaver 00:04:00 Understanding Color Management Why Color Management 00:03:00 Calibrating a Monitor 00:04:00 Calibrating a Printer 00:03:00 Loading Profiles into PSDs 00:02:00 Conclusion Course Recap 00:03:00 Adobe Photoshop CC Advanced Introduction Introduction FREE 00:03:00 Processing Raw Images What is the RAW Format 00:04:00 Understanding White Balance 00:05:00 Setting Exposure 00:07:00 Working with Color and Clarity 00:03:00 Working with Adobe Camera Raw Updating Adobe Camera Raw 00:01:00 Using the Before and After Views 00:05:00 Resetting the Sliders 00:01:00 Understanding the Workflow Options 00:04:00 Setting the Camera Raw Preferences 00:03:00 Working with the Tools Understanding the White Board Tool 00:03:00 Using the Color Sampler 00:01:00 Working with the Targeted Adjustment Tool 00:02:00 Cropping Images 00:03:00 Applying Straightening 00:01:00 Using the Spot Removal Tool 00:05:00 Applying the Red Eye Tool 00:03:00 Understanding the Adjustment Brush 00:04:00 Using the Graduated Filter 00:02:00 Applying the Radial Filter 00:02:00 Rotating Images 00:01:00 Using Advanced Exposure Settings and Sharpening Using Curves 00:03:00 Understanding Sharpening and Noise 00:03:00 Creating Grayscale Images 00:03:00 Using Split Toning 00:03:00 Managing Corrections and Effects Enabling Lens Profiles 00:03:00 Using Effects 00:02:00 Adding Grain 00:02:00 Applying Post Crop Vignette 00:02:00 Using Camera Calibration 00:03:00 Saving Presets 00:02:00 Applying Snapshots 00:02:00 Creating Image Adjustments Using Adjustment Layers 00:02:00 Painting Layer Masks 00:05:00 Discovering Plugins for Photoshop What are Plugins 00:04:00 Using the Nik Collection 00:08:00 Using HDR Pro Effex 00:06:00 Using On1 Effects 00:04:00 Exploring Workflows Introudcing the Workshop Videos 00:04:00 Processing a Landscape Image 00:13:00 Processing a Macro Image 00:09:00 Processing a City 00:11:00 Conclusion Course Recap 00:02:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

87% of hiring managers believe digital design skills are essential in recruiting creative professionals

Course overview Learn multivariable calculus with this Calculus 3 (Multivariable) Masterclass course. In this course, you will understand the complexities of multivariable calculus and solve various problems. The Calculus 3 (Multivariable) Masterclass course will go over the fundamental ideas about multivariable functions. It will introduce you to analytical geometry and explain where it's used. You will identify the distance formula to calculate distance between two points and learn how to calculate dot and cross products. In addition, you will learn about conic sections, topology, partial derivatives and vector-valued functions and use them to solve problems. Many practice problems with solutions are included in this course to improve your problem-solving abilities. Learning outcomes Learn about limit, continuity and differentiability Know how to graph a parabola using conic sections Understand what is a paraboloid in calculus Identify the differentiation rules and use them to solve problems Learn about different coordinate systems Be able to compute a composite function's derivative using chain rule Learn how to use Taylor's formula Who Is This Course For? Anyone interested in learning Calculus most efficiently can take this Calculus 3 (Multivariable) Masterclass course. The skills gained from this training will provide excellent opportunities for career advancement. Entry Requirement This course is available to all learners of all academic backgrounds. Learners should be aged 16 or over. Good understanding of English language, numeracy and ICT skills are required to take this course. Certification After you have successfully completed the course, you will obtain an Accredited Certificate of Achievement. And, you will also receive a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy for £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why Choose Us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos and materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; United Kingdom & internationally recognized accredited qualification; Access to course content on mobile, tablet and desktop from anywhere, anytime; Substantial career advancement opportunities; 24/7 student support via email. Career Path The Calculus 3 (Multivariable) Masterclass course provides essential skills that will make you more effective in your role. It would be beneficial for any related profession in the industry, such as: Math's Teacher

Overview This comprehensive course on Spatial Analysis in ArcGIS will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Spatial Analysis in ArcGIS comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? At the end of the course there will be an online written test, which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Spatial Analysis in ArcGIS. It is available to all students, of all academic backgrounds. Requirements Our Spatial Analysis in ArcGIS is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 2 sections • 11 lectures • 01:56:00 total length •Module 01: Point Density Analysis: 00:10:00 •Module 02: Raster Calculator and Vector Isolation: 00:12:00 •Module 03: Raster to Topography: 00:12:00 •Module 04: Raster Reclassification: 00:14:00 •Module 05: Raster Overlay: 00:13:00 •Module 06: Slope Analysis and Hydrology tools: 00:11:00 •Module 07: Introduction to TIFF Files: 00:12:00 •Module 08: Introduction to 3D Surfaces: 00:12:00 •Module 09: Satellite Images and TIN Surfaces: 00:12:00 •Module 10: Exercise: 00:08:00 •Assignment - Spatial Analysis in ArcGIS: 00:00:00

Take your first step toward Natural Language Processing with this beginner-to-pro course. Gain an in-depth understanding of deep learning models for NLP with the help of examples. Learn the essential concepts from the absolute beginning with complete unraveling along with examples in Python.

Level 2- Two Endorsed Training | QLS Hard Copy Certificate Included | Plus 5 CPD Courses | Lifetime Access

Level 2 & 3 Endorsed Training | QLS Hard Copy Certificate Included | Plus 5 CPD Courses | Lifetime Access

Prepare for a career in the high-growth field of IT, no experience or degree is required! With more businesses shifting online, the demand for tech professionals is at an all-time high in the UK. Software Developers, Project managers, Cybersecurity analysts, Cloud architects, and Data analysts are just a few of them. Tech giants like Google, Amazon, Meta, Apple, and Microsoft always welcome skilled IT professionals. The salary ranges vary with skill and experience, with an average of £50K in relevant sectors. And the best thing is if you are good enough, you can even work from home. So enrol in this Complete C# Unity Game Developer 3D course to start your journey to success now! Along with this Complete C# Unity Game Developer 3D course, you will get 19 Premium courses, an originalHardcopy, 20 PDF certificates (Main Course + Additional Courses) Student ID card as gifts. This Complete C# Unity Game Developer 3D Bundle Consists of the following Premium courses: Course 01: Basic Game Development with Unity Course 02: Basic C# Coding Course 03: C# Basics Course 04: Maya & Unity 3D: Modeling Environments for Mobile Games Course 05: Maya & Unity 3D: Modeling Lowpoly Tree for Mobile Games Course 06: Create a Game With Gamemaker Studio 2 Course 07: Publish Game Assets to the Unity & Unreal Marketplace for Passive Income Course 08: Javascript Programming for Beginners Course 09: Game Development using Cocos2d-x v3 C++ Course 10: Cocos2d-x v3 JavaScript: Game Development Course 11: Modern OpenGL 3D Game Course 12: Design 2D Game Characters With Inkscape Course 13: Develop 2D Game UI Using Inkscape Course 14: Video Game Design Course Course 15: Blender 3D - Create a Cartoon Character Course 16: Dynamic 2D Video Game Animation Course 17: Modular Game Art Creation Course 18: Vector Game Art Creation Course 19: HTML and CSS Coding: Beginner to Advanced Course 20: Blender to Unreal Engine 5 The bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Complete C# Unity Game Developer 3D expertise and essential knowledge, which will assist you in reaching your goal. Moreover, you can learn from any place in your own time without travelling for classes. Course Curriculum: Course 01: Basic Game Development with Unity Module 01: Introduction Module 02: Project Files Module 03: Installing Unity Module 04: Creating a Project Module 05: Unity Editor Module 06: Scene Navigator Module 07: Game Object Module 08: Moving Object Module 09: Rotating Object Module 10: Scaling Object and Parenting Module 11: Materials Module 12: Prefabs Module 13: Introduction to Scripting Module 14: Variable Module 15: Operator Module 16: Condition Part-1 Module 17: Condition Part-2 Module 18: Vectors Module 19: Balloon Popper Part-1 Module 20: Balloon Popper Part-2 Module 21: Building Your Game Module 22: Conclusion Certificate: PDF Certificate: Free (Previously it was £6*11 = £66) Hard Copy Certificate: Free (For The Title Course: Previously it was £10) CPD 215 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Complete C# Unity Game Developer 3D bundle. Requirements This Complete C# Unity Game Developer 3D course has been designed to be fully compatible with tablets and smartphones. Career path Having this expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Basic Game Development with Unity) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Complete Python Machine Learning & Data Science Fundamentals there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Complete Python Machine Learning & Data Science Fundamentals course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00