Python and R for Machine Learning & Deep Learning

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Free Download Python and R for Machine Learning & Deep Learning
Published 6/2024
Created by Manuel Ernesto Cambota
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 252 Lectures ( 32h 9m ) | Size: 12.4 GB

Learn Machine Learning and Deep Learning using Python and R in 2024
What you'll learn:
Basics to advanced Python programming
Data manipulation with Pandas
Visualization with Matplotlib and Seaborn
Fundamentals of R
Statistical modeling in R
Introduction to neural networks
Building models with TensorFlow and Keras
Convolutional and Recurrent Neural Networks
Comprehensive understanding of machine learning and deep learning
Requirements:
No Pre-requisites
Description:
Welcome to the gateway to your journey into Python for Machine Learning & Deep Learning!Unlock the power of Python and delve into the realms of Machine Learning and Deep Learning with our comprehensive course. Whether you're a beginner eager to step into the world of artificial intelligence or a seasoned professional looking to enhance your skills, this course is designed to cater to all levels of expertise.What sets this course apart?Comprehensive Curriculum: Our meticulously crafted curriculum covers all the essential concepts of Python programming, machine learning algorithms, and deep learning architectures. From the basics to advanced techniques, we've got you covered.Hands-On Projects: Theory is important, but practical experience is paramount. Dive into real-world projects that challenge you to apply what you've learned and reinforce your understanding.Expert Guidance: Learn from industry expert who has years of experience in the field. Benefit from his insights, tips, and best practices to accelerate your learning journey.Interactive Learning: Engage in interactive lessons, quizzes, and exercises designed to keep you motivated and actively involved throughout the course.Flexibility: Life is busy, and we understand that. Our course offers flexible scheduling options, allowing you to learn at your own pace and convenience.Career Opportunities: Machine Learning and Deep Learning are in high demand across various industries. By mastering these skills, you'll open doors to exciting career opportunities and potentially higher earning potential.Are you ready to embark on an exhilarating journey into the world of Python for Machine Learning & Deep Learning? Enroll now and take the first step towards becoming a proficient AI practitioner!
Who this course is for:
IT Professionals: Broaden your career prospects by transitioning into the field of data science
Students: Whether you're an undergraduate or a postgraduate student, this course provides a robust framework for understanding machine learning and deep learning concepts
Career Changers: Looking to pivot into a rapidly growing field with immense opportunities? This course will provide you with the necessary skills and knowledge to make a successful transition into data science and machine learning.
Entrepreneurs and Business Owners: Leverage the power of machine learning and deep learning to drive business innovation and efficiency. Understand how to implement data-driven strategies to improve decision-making and gain a competitive edge.
Anyone Interested in Data Science: If you have a passion for data and a desire to learn how to extract valuable insights from it, this course is for you. Gain a comprehensive understanding of machine learning and deep learning, regardless of your current level of expertise.
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12.41 GB | 20min 16s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

FileName :1 Overview.mp4 | Size: (20.45 MB)
FileName :1 Project - Introduction.mp4 | Size: (47.68 MB)
FileName :10 Project in R - Data Augmentation.mp4 | Size: (61.39 MB)
FileName :11 Project in R - Validation Performanc.mp4 | Size: (26.77 MB)
FileName :12 Project - Data Augmentation Preprocessing.mp4 | Size: (42.62 MB)
FileName :13 Project - Data Augmentation Training and Results.mp4 | Size: (56.98 MB)
FileName :3 Project - Data Preprocessing in Python.mp4 | Size: (76.01 MB)
FileName :4 Project - Training CNN model in Python.mp4 | Size: (68.96 MB)
FileName :5 Project in Python - model results.mp4 | Size: (22.18 MB)
FileName :6 Project in R - Data Preprocessing.mp4 | Size: (96.68 MB)
FileName :7 CNN Project in R - Structure and Compile.mp4 | Size: (51.12 MB)
FileName :8 Project in R - Training.mp4 | Size: (27.21 MB)
FileName :9 Project in R - Model Performance.mp4 | Size: (25.96 MB)
FileName :1 ILSVRC.mp4 | Size: (20.27 MB)
FileName :2 LeNET.mp4 | Size: (7.48 MB)
FileName :3 VGG16NET.mp4 | Size: (10.05 MB)
FileName :4 GoogLeNet.mp4 | Size: (21 MB)
FileName :5 Transfer Learning.mp4 | Size: (30.2 MB)
FileName :6 Project - Transfer Learning - VGG16.mp4 | Size: (135.62 MB)
FileName :7 Project - Transfer Learning - VGG16 (Implementation).mp4 | Size: (111.89 MB)
FileName :8 Project - Transfer Learning - VGG16 (Performance).mp4 | Size: (71.64 MB)
FileName :1 Introduction.mp4 | Size: (11.96 MB)
FileName :2 Time Series Forecasting - Use cases.mp4 | Size: (25.71 MB)
FileName :3 Forecasting model creation - Steps.mp4 | Size: (9.57 MB)
FileName :4 Forecasting model creation - Steps 1 (Goal).mp4 | Size: (33.16 MB)
FileName :5 Time Series - Basic Notations.mp4 | Size: (60.79 MB)
FileName :1 Data Loading in Python.mp4 | Size: (110.77 MB)
FileName :10 Exponential Smoothing.mp4 | Size: (8.07 MB)
FileName :11 White Noise.mp4 | Size: (10.99 MB)
FileName :12 Random Walk.mp4 | Size: (20.33 MB)
FileName :13 Decomposing Time Series in Python.mp4 | Size: (62.37 MB)
FileName :14 Differencing.mp4 | Size: (31.77 MB)
FileName :15 Differencing in Python.mp4 | Size: (117.74 MB)
FileName :16 Test Train Split in Python.mp4 | Size: (59.07 MB)
FileName :17 Naive (Persistence) model in Python.mp4 | Size: (44.29 MB)
FileName :18 Auto Regression Model - Basics.mp4 | Size: (16.57 MB)
FileName :19 Auto Regression Model creation in Python.mp4 | Size: (55.45 MB)
FileName :2 Time Series - Visualization Basics.mp4 | Size: (62.97 MB)
FileName :20 Auto Regression with Walk Forward validation in Python.mp4 | Size: (51.54 MB)
FileName :21 Moving Average model -Basics.mp4 | Size: (23.67 MB)
FileName :22 Moving Average model in Python.mp4 | Size: (58.37 MB)
FileName :3 Time Series - Visualization in Python.mp4 | Size: (169.83 MB)
FileName :4 Time Series - Feature Engineering Basics.mp4 | Size: (58.46 MB)
FileName :5 Time Series - Feature Engineering in Python.mp4 | Size: (116.95 MB)
FileName :6 Time Series - Upsampling and Downsampling.mp4 | Size: (16.55 MB)
FileName :7 Time Series - Upsampling and Downsampling in Python.mp4 | Size: (102.2 MB)
FileName :8 Time Series - Power Transformation.mp4 | Size: (14.67 MB)
FileName :9 Moving Average.mp4 | Size: (37.88 MB)
FileName :1 ACF and PACF.mp4 | Size: (40.59 MB)
FileName :2 ARIMA model - Basics.mp4 | Size: (20.71 MB)
FileName :3 ARIMA model in Python.mp4 | Size: (76.55 MB)
FileName :4 ARIMA model with Walk Forward Validation in Python.mp4 | Size: (33.13 MB)
FileName :1 SARIMA model.mp4 | Size: (38.45 MB)
FileName :2 SARIMA model in Python.mp4 | Size: (69.15 MB)
FileName :3 Stationary time Series.mp4 | Size: (5.3 MB)
FileName :1 Installing Python & Anaconda.mp4 | Size: (16.37 MB)
FileName :2 Jupyter Overview.mp4 | Size: (40.03 MB)
FileName :3 Python Basics.mp4 | Size: (12.44 MB)
FileName :4 Python Basics 2.mp4 | Size: (63.47 MB)
FileName :5 Python Basics 3.mp4 | Size: (59.72 MB)
FileName :6 Numpy.mp4 | Size: (44.32 MB)
FileName :7 Pandas.mp4 | Size: (50.95 MB)
FileName :8 Seaborn.mp4 | Size: (42.26 MB)
FileName :1 Installing R & Studio.mp4 | Size: (37.59 MB)
FileName :2 R & R Studio - Basics.mp4 | Size: (36.95 MB)
FileName :3 Packages in R.mp4 | Size: (84.64 MB)
FileName :4 Inbuilt datasets of R.mp4 | Size: (41.53 MB)
FileName :5 Manual data entry.mp4 | Size: (25.96 MB)
FileName :6 Importing from CSV or Text files.mp4 | Size: (61.15 MB)
FileName :7 Barplots.mp4 | Size: (98.25 MB)
FileName :8 Histograms.mp4 | Size: (42.31 MB)
FileName :1 Types of Data.mp4 | Size: (21.73 MB)
FileName :2 Types of Statistics.mp4 | Size: (10.57 MB)
FileName :3 Describing data Graphically.mp4 | Size: (67.26 MB)
FileName :4 Measures of Centers.mp4 | Size: (39.37 MB)
FileName :5 Measures of Dispersion.mp4 | Size: (23.55 MB)
FileName :1 Introduction to Machine Learning.mp4 | Size: (107.24 MB)
FileName :10 EDD in R.mp4 | Size: (99.33 MB)
FileName :100 Random Forest in R.mp4 | Size: (30.37 MB)
FileName :101 Boosting.mp4 | Size: (29.4 MB)
FileName :102 Ensemble technique 3a - Boosting in Python.mp4 | Size: (42.22 MB)
FileName :103 Gradient Boosting in R.mp4 | Size: (68.93 MB)
FileName :104 Ensemble technique 3b - AdaBoost in Python.mp4 | Size: (33.49 MB)
FileName :105 AdaBoosting in R.mp4 | Size: (89.46 MB)
FileName :106 Ensemble technique 3c - XGBoost in Python.mp4 | Size: (79.3 MB)
FileName :107 XGBoosting in R.mp4 | Size: (163.42 MB)
FileName :108 Content Flow.mp4 | Size: (8.36 MB)
FileName :109 Concept of a Hyperplane.mp4 | Size: (28.5 MB)
FileName :11 Outlier Treatment.mp4 | Size: (23.47 MB)
FileName :110 Maximum Margin Classifier.mp4 | Size: (21.99 MB)
FileName :111 Limitations of Maximum Margin Classifier.mp4 | Size: (10.06 MB)
FileName :112 Support Vector classifiers.mp4 | Size: (55.67 MB)
FileName :113 Limitations of Support Vector Classifiers.mp4 | Size: (10.65 MB)
FileName :114 Kernel Based Support Vector Machines.mp4 | Size: (39.5 MB)
FileName :115 Regression and Classification Models.mp4 | Size: (4.06 MB)
FileName :116 Importing and preprocessing data in Python.mp4 | Size: (26.62 MB)
FileName :117 Standardizing the data.mp4 | Size: (39.29 MB)
FileName :118 SVM based Regression Model in Pytho.mp4 | Size: (71.96 MB)
FileName :119 Classification model - Preprocessing.mp4 | Size: (48.78 MB)
FileName :12 Outlier Treatment in Python.mp4 | Size: (74.03 MB)
FileName :120 Classification model - Standardizing the data.mp4 | Size: (10.35 MB)
FileName :121 SVM Based classification model.mp4 | Size: (66.24 MB)
FileName :122 Hyper Parameter Tuning.mp4 | Size: (61.09 MB)
FileName :123 Polynomial Kernel with Hyperparameter Tuning.mp4 | Size: (24.16 MB)
FileName :124 Radial Kernel with Hyperparameter Tuning.mp4 | Size: (39.83 MB)
FileName :125 Importing and preprocessing data in R.mp4 | Size: (53.5 MB)
FileName :126 Classification SVM model using Linear Kernel.mp4 | Size: (139.78 MB)
FileName :127 Hyperparameter Tuning for Linear Kernel.mp4 | Size: (61.15 MB)
FileName :128 Polynomial Kernel with Hyperparameter Tuning.mp4 | Size: (83.18 MB)
FileName :129 Radial Kernel with Hyperparameter Tuning.mp4 | Size: (56.78 MB)
FileName :13 Outlier Treatment in R.mp4 | Size: (31.36 MB)
FileName :130 SVM based Regression Model in R.mp4 | Size: (107.74 MB)
FileName :14 Missing Value Imputation.mp4 | Size: (23.89 MB)
FileName :15 Missing Value Imputation in Python.mp4 | Size: (24.69 MB)
FileName :16 Missing Value imputation in R.mp4 | Size: (26.55 MB)
FileName :17 Seasonality in Data.mp4 | Size: (16.52 MB)
FileName :18 Bi-variate analysis and Variable transformation.mp4 | Size: (96.74 MB)
FileName :19 Variable transformation and deletion in Python.mp4 | Size: (46.19 MB)
FileName :2 Building a Machine Learning Model.mp4 | Size: (38.11 MB)
FileName :20 Variable transformation in R.mp4 | Size: (56.94 MB)
FileName :21 Non-usable variables.mp4 | Size: (18.61 MB)
FileName :22 Dummy variable creation Handling qualitative data.mp4 | Size: (35.79 MB)
FileName :23 Dummy variable creation in Python.mp4 | Size: (27.63 MB)
FileName :24 Dummy variable creation in R.mp4 | Size: (46.42 MB)
FileName :25 Correlation Analysis.mp4 | Size: (69.09 MB)
FileName :26 Correlation Analysis in Python.mp4 | Size: (58.88 MB)
FileName :27 Correlation Matrix in R.mp4 | Size: (86.21 MB)
FileName :28 The Problem Statement.mp4 | Size: (9.5 MB)
FileName :29 Basic Equations and Ordinary Least Squares (OLS) method.mp4 | Size: (41.78 MB)
FileName :3 Gathering Business Knowledge.mp4 | Size: (20.24 MB)
FileName :30 Assessing accuracy of predicted coefficients.mp4 | Size: (90.66 MB)
FileName :31 Assessing Model Accuracy RSE and R squared.mp4 | Size: (41.92 MB)
FileName :32 Simple Linear Regression in Python.mp4 | Size: (65.7 MB)
FileName :33 Simple Linear Regression in R.mp4 | Size: (39.97 MB)
FileName :34 Multiple Linear Regression.mp4 | Size: (33.11 MB)
FileName :35 The F - statistic.mp4 | Size: (54.04 MB)
FileName :36 Interpreting results of Categorical variables.mp4 | Size: (21.26 MB)
FileName :37 Multiple Linear Regression in Python.mp4 | Size: (70.5 MB)
FileName :38 Multiple Linear Regression in R.mp4 | Size: (63.53 MB)
FileName :39 Test-train split.mp4 | Size: (40.41 MB)
FileName :4 Data Exploration.mp4 | Size: (19.9 MB)
FileName :40 Bias Variance trade-off.mp4 | Size: (23.88 MB)
FileName :41 Test train split in Python.mp4 | Size: (45.27 MB)
FileName :42 Test-Train Split in R.mp4 | Size: (75.61 MB)
FileName :43 Regression models other than OLS.mp4 | Size: (15.36 MB)
FileName :44 Subset selection techniques.mp4 | Size: (76.28 MB)
FileName :45 SubShrinkage methods Ridge and Lassoset selection in R.mp4 | Size: (31.19 MB)
FileName :46 Ridge regression and Lasso in Python.mp4 | Size: (132.2 MB)
FileName :47 Heteroscedasticity.mp4 | Size: (14.25 MB)
FileName :48 Ridge Regression and Lasso in R.mp4 | Size: (104.25 MB)
FileName :49 importing the data into Python.mp4 | Size: (21.9 MB)
FileName :5 Dataset & Data Dictionary.mp4 | Size: (74.89 MB)
FileName :50 Importing the data into R.mp4 | Size: (13.72 MB)
FileName :51 Three Classifiers and the Problem statement.mp4 | Size: (20.13 MB)
FileName :52 Why can't we use Linear Regression.mp4 | Size: (15.63 MB)
FileName :53 Logistic Regression.mp4 | Size: (31.17 MB)
FileName :54 Training a Simple Logistic Model in Python.mp4 | Size: (47.67 MB)
FileName :55 Training a Simple Logistic model in R.mp4 | Size: (16.11 MB)
FileName :56 Result of Simple Logistic Regression.mp4 | Size: (25.93 MB)
FileName :57 Logistic with multiple predictors.mp4 | Size: (7.92 MB)
FileName :58 Training multiple predictor Logistic model in Python.mp4 | Size: (26.79 MB)
FileName :59 Training multiple predictor Logistic model in R.mp4 | Size: (16.1 MB)
FileName :6 Importing Data in Python.mp4 | Size: (28.14 MB)
FileName :60 Confusion Matrix.mp4 | Size: (20.17 MB)
FileName :61 Creating Confusion Matrix in Python.mp4 | Size: (53.73 MB)
FileName :62 Evaluating performance of model.mp4 | Size: (34.27 MB)
FileName :63 Evaluating model performance in Python.mp4 | Size: (9.13 MB)
FileName :64 Predicting probabilities, assigning classes and making Confusion Matrix in R.mp4 | Size: (55.44 MB)
FileName :65 Linear Discriminant Analysis.mp4 | Size: (38.88 MB)
FileName :66 LDA in Python.mp4 | Size: (12.06 MB)
FileName :67 Linear Discriminant Analysis in R.mp4 | Size: (74.82 MB)
FileName :68 Test-Train Split.mp4 | Size: (37.33 MB)
FileName :69 Test-Train Split in Python.mp4 | Size: (32.94 MB)
FileName :7 Importing the dataset into R.mp4 | Size: (13.32 MB)
FileName :70 Test-Train Split in R.mp4 | Size: (73.59 MB)
FileName :71 K-Nearest Neighbors classifier.mp4 | Size: (73.38 MB)
FileName :72 K-Nearest Neighbors in Python Part 1.mp4 | Size: (39.45 MB)
FileName :73 K-Nearest Neighbors in Python Part 2.mp4 | Size: (46.18 MB)
FileName :74 K-Nearest Neighbors in R.mp4 | Size: (64.36 MB)
FileName :75 Understanding the results of classification models.mp4 | Size: (39.72 MB)
FileName :76 Summary of the three models.mp4 | Size: (21.26 MB)
FileName :77 Basics of Decision Trees.mp4 | Size: (40.25 MB)
FileName :78 Understanding a Regression Tree.mp4 | Size: (41.22 MB)
FileName :79 Stopping criteria for controlling tree growth.mp4 | Size: (13.07 MB)
FileName :8 Univariate analysis and EDD.mp4 | Size: (23.51 MB)
FileName :80 Importing the Data set into Python.mp4 | Size: (26.68 MB)
FileName :81 Importing the Data set into R.mp4 | Size: (43.99 MB)
FileName :82 Missing value treatment in Python.mp4 | Size: (18.65 MB)
FileName :83 Dummy Variable creation in Python.mp4 | Size: (26.22 MB)
FileName :84 Dependent- Independent Data split in Python.mp4 | Size: (15.34 MB)
FileName :85 Test-Train split in Python.mp4 | Size: (24.76 MB)
FileName :86 Splitting Data into Test and Train Set in R.mp4 | Size: (43.92 MB)
FileName :87 Creating Decision tree in Python.mp4 | Size: (18.67 MB)
FileName :88 Building a Regression Tree in R.mp4 | Size: (103.96 MB)
FileName :89 Evaluating model performance in Python.mp4 | Size: (16.3 MB)
FileName :9 EDD in Python.mp4 | Size: (65.95 MB)
FileName :90 Plotting decision tree in Python.mp4 | Size: (21.54 MB)
FileName :91 Pruning a tree.mp4 | Size: (17.36 MB)
FileName :92 Pruning a tree in Python.mp4 | Size: (77.7 MB)
FileName :93 Pruning a Tree in R.mp4 | Size: (83.91 MB)
FileName :94 Ensemble technique 1 - Bagging.mp4 | Size: (27.47 MB)
FileName :95 Ensemble technique 1 - Bagging in Python.mp4 | Size: (79.37 MB)
FileName :96 Bagging in R.mp4 | Size: (59.29 MB)
FileName :97 Ensemble technique 2 - Random Forests.mp4 | Size: (17.7 MB)
FileName :98 Ensemble technique 2 - Random Forests in Python.mp4 | Size: (50 MB)
FileName :99 Using Grid Search in Python.mp4 | Size: (84.35 MB)
FileName :1 Introduction to Neural Networks and Course flow.mp4 | Size: (29.36 MB)
FileName :2 Perceptron.mp4 | Size: (44.42 MB)
FileName :3 Activation Functions.mp4 | Size: (34.37 MB)
FileName :4 Python - Creating Perceptron model.mp4 | Size: (90.79 MB)
FileName :5 Basic Terminologies.mp4 | Size: (40.73 MB)
FileName :6 Gradient Descent.mp4 | Size: (60.9 MB)
FileName :7 Back Propagation.mp4 | Size: (121.96 MB)
FileName :8 Some Important Concepts.mp4 | Size: (61.03 MB)
FileName :9 Hyperparameter.mp4 | Size: (44.67 MB)
FileName :1 Keras and Tensorflow.mp4 | Size: (14.6 MB)
FileName :10 Using Functional API for complex architectures.mp4 | Size: (96.4 MB)
FileName :11 Saving - Restoring Models and Using Callbacks.mp4 | Size: (162.45 MB)
FileName :12 Hyperparameter Tuning.mp4 | Size: (58.92 MB)
FileName :2 Installing Tensorflow and Keras.mp4 | Size: (20.5 MB)
FileName :3 Dataset for classification.mp4 | Size: (58.04 MB)
FileName :4 Normalization and Test-Train split.mp4 | Size: (48.39 MB)
FileName :5 Different ways to create ANN using Keras.mp4 | Size: (11 MB)
FileName :6 Building the Neural Network using Keras.mp4 | Size: (82.93 MB)
FileName :7 Compiling and Training the Neural Network model.mp4 | Size: (87.68 MB)
FileName :8 Evaluating performance and Predicting using Keras.mp4 | Size: (74.43 MB)
FileName :9 Building Neural Network for Regression Problem.mp4 | Size: (164.54 MB)
FileName :1 Installing Keras and Tensorflow.mp4 | Size: (24.9 MB)
FileName :2 Data Normalization and Test-Train Split.mp4 | Size: (124.64 MB)
FileName :3 Building,Compiling and Training.mp4 | Size: (145.87 MB)
FileName :4 Evaluating and Predicting.mp4 | Size: (111.6 MB)
FileName :5 ANN with NeuralNets Package.mp4 | Size: (95.2 MB)
FileName :6 Building Regression Model with Functional API.mp4 | Size: (146.55 MB)
FileName :7 Complex Architectures using Functional API.mp4 | Size: (88.57 MB)
FileName :8 Saving - Restoring Models and Using Callbacks.mp4 | Size: (242.47 MB)
FileName :1 CNN Introduction.mp4 | Size: (56.12 MB)
FileName :10 Comparison - Pooling vs Without Pooling in Python.mp4 | Size: (62.28 MB)
FileName :11 CNN on MNIST Fashion Dataset - Model Architecture.mp4 | Size: (7.42 MB)
FileName :12 Data Preprocessin.mp4 | Size: (75.93 MB)
FileName :13 Creating Model Architecture.mp4 | Size: (82.31 MB)
FileName :14 Compiling and training.mp4 | Size: (36.88 MB)
FileName :15 Model Performance.mp4 | Size: (77.5 MB)
FileName :16 Comparison - Pooling vs Without Pooling in R.mp4 | Size: (49.81 MB)
FileName :2 Stride.mp4 | Size: (18.33 MB)
FileName :3 Padding.mp4 | Size: (32.79 MB)
FileName :4 Filters and Feature maps.mp4 | Size: (54.99 MB)
FileName :5 Channels.mp4 | Size: (70.82 MB)
FileName :6 PoolingLayer.mp4 | Size: (47.23 MB)
FileName :7 CNN model in Python - Preprocessing.mp4 | Size: (42.87 MB)
FileName :8 CNN model in Python - structure and Compile.mp4 | Size: (45.12 MB)
FileName :9 CNN model in Python - Training and results.mp4 | Size: (58.1 MB)

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