Coursera - Mastering Ai: Neural Nets, Vision System, Speech Recognition Specialization

[lesedev317]

Coursera - Mastering Ai: Neural Nets, Vision System, Speech Recognition Specialization
Released 2/2025
By Edureka
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + subtitle | Duration: 323 Lessons ( 26h 16m ) | Size: 6.76 GB​

Master AI to Build Intelligent Systems and Drive Innovation
What you'll learn
Analyze and apply fundamental Python functions and methods.
Utilize and apply various machine learning models effectively.
Design and optimize neural networks for AI applications.
Explain and implement image, video, and audio processing methods.
Skills you'll gain
Association Rule Learning
Model Optimization
Computer Vision
Statistical Inference
Python (Programming Language)
Deep Learning
Recommendation Engines
Machine Learning
Artificial Intelligence
Model Evaluation
Images and Video Processing
Data Manipulation with NumPy and Pandas
Association Rule Mining and Recommendation
Data Analysis
Supervised Learning
Linear Regression
Data Visualization
Statistical Analysis
Data Manipulation
Implementing Optimizing Algorithms
Manipulating complex datasets
Analyzing different types frameworks
Building SLP and MLP models
Creating models with different algorithms
Image and Video Processing with OpenCV
Speech Recognition
Speech Analysis and Processing
Morphological Image Operations
Begin your journey with the Mastering AI specialization, designed for both aspiring and experienced professionals. This program equips you with essential skills in artificial intelligence, machine learning, and deep learning to develop cutting-edge solutions.
Explore key concepts such as neural networks, statistical foundations, predictive modeling, and AI-driven computer vision and speech recognition. Through hands-on projects and real-world case studies, gain the expertise to build intelligent models, optimize deep learning architectures, and apply AI to solve complex challenges.
The specialization comprises four comprehensive courses
Python and Statistics Foundations: Build a strong foundation in Python programming, probability, and statistical analysis for AI applications.
Applied Machine Learning with Python: Learn to develop, train, and optimize machine learning models to extract insights and drive AI solutions.
Practical Deep Learning with Python: Master deep learning techniques, neural networks, and advanced model optimization for real-world AI applications.
AI Applications: Computer Vision and Speech Recognition: Explore AI-driven image processing and speech recognition technologies.
By the end of this program, you'll be prepared to design and implement AI solutions, harness the power of deep learning, and advance your career in artificial intelligence. Join us to unlock the full potential of AI and drive innovation across industries!
Applied Learning Project
Learners will acquire proficiency in building complex machine learning and deep learning models to solve challenging problems while demonstrating a high level of problem-solving skills. Learners will learn to program using Python, clean and transform data using various data preprocessing methods, and apply statistical and inferential modeling.
Learners will also gain expertise in different machine learning techniques. Additionally, they will explore deep learning techniques such as Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Faster R-CNN, and other advanced architectures.
The curriculum encompasses knowledge of AI processing for video, audio, and speech recognition. Learners will progress from basic to advanced programming concepts for handling AI-related tasks. Their ability to apply acquired knowledge will be demonstrated through individual projects, serving as the culmination of their educational journey.

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[0dayddl]

4.66 GB | 00:00:15 | mp4 | 3840X2160 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

02 course-introduction.mp4 (13.11 MB)
04 speech-recognition-technology.mp4 (17.67 MB)
05 computer-vision-application.mp4 (21.26 MB)
07 ai-responsibility-pyramid.mp4 (18.98 MB)
09 evolution-of-speech-analysis.mp4 (15.26 MB)
10 what-is-opencv.mp4 (17.82 MB)
01 installing-opencv-on-windows.mp4 (11.09 MB)
01 operations-on-opencv.mp4 (8.79 MB)
04 demonstration-gaussian-blur.mp4 (21.56 MB)
05 demonstration-edge-detection-and-conversion.mp4 (21.36 MB)
06 demonstration-image-thresholding-binary-image.mp4 (17.13 MB)
07 demonstration-different-methods-of-thresholding.mp4 (24.79 MB)
08 demonstration-practical-use-cases.mp4 (10.48 MB)
09 what-is-adaptive-thresholding.mp4 (12.3 MB)
10 demonstration-of-global-adaptive-threshold.mp4 (14.6 MB)
01 morphological-operations.mp4 (15.41 MB)
02 morphological-operations-in-opencv.mp4 (11.78 MB)
03 demonstration-opening-dilation-and-erosion.mp4 (23.22 MB)
05 blackhat-and-whitehat-transformations.mp4 (15.11 MB)
06 demonstration-whitehat-tophat.mp4 (13.87 MB)
07 demonstration-blackhat.mp4 (18.22 MB)
01 summary-of-computer-vision-with-opencv.mp4 (23.1 MB)
01 video-processing.mp4 (8.46 MB)
05 demonstration-saving-the-frames.mp4 (32.23 MB)
06 demonstration-loading-the-data.mp4 (20.23 MB)
08 demonstration-histogram-matching.mp4 (27.07 MB)
11 demonstration-differences-in-images.mp4 (15.59 MB)
01 introduction-to-speech-audio-data.mp4 (11.02 MB)
03 processing-speech.mp4 (18.26 MB)
04 speech-production.mp4 (20.63 MB)
05 difficulties-in-analyzing-speech.mp4 (17.91 MB)
06 working-of-sound-waves.mp4 (14.68 MB)
07 adc-and-sample-rate-bit-rate.mp4 (12.01 MB)
09 demonstration-generating-sound.mp4 (33.68 MB)
10 demonstration-spectrogram.mp4 (27.63 MB)
12 summary-of-audio-file-analysis.mp4 (7.38 MB)
01 human-speech.mp4 (18.91 MB)
02 speech-waveform.mp4 (18.02 MB)
03 digital-signal-processing.mp4 (18.18 MB)
11 tremor-detection.mp4 (6.51 MB)
01 Traffic.mp4 (185.81 MB)
01 highway.mp4 (4.98 MB)
02 course-introduction.mp4 (14.8 MB)
03 machine-learning-in-industry.mp4 (15.59 MB)
04 how-companies-use-machine-learning.mp4 (18.89 MB)
01 machine-learning-process.mp4 (14.84 MB)
02 steps-in-machine-learning.mp4 (13.79 MB)
03 types-of-machine-learning.mp4 (21.81 MB)
01 introduction-to-linear-regression.mp4 (18.61 MB)
02 real-life-examples.mp4 (22.05 MB)
03 calculating-ols.mp4 (40.38 MB)
04 equation-of-ols.mp4 (16.29 MB)
05 assumptions-in-linear-regression.mp4 (22.41 MB)
06 demonstration-setting-up-the-model.mp4 (23.13 MB)
07 calculating-r-square-and-rmse.mp4 (28.36 MB)
08 residual-plot-and-q-q-plot.mp4 (9.96 MB)
09 cooks-distance.mp4 (22.59 MB)
10 real-life-examples-of-logistic-regression.mp4 (21.03 MB)
11 what-is-logistic-regression.mp4 (26.84 MB)
12 cost-function.mp4 (13.93 MB)
13 assumptions-in-logistic-regression.mp4 (19.09 MB)
14 demonstration-of-logistic-regression-transforming-data.mp4 (29.9 MB)
15 demonstration-of-logistic-regression-developing-the-model.mp4 (18.35 MB)
01 confusion-matrix.mp4 (12.22 MB)
02 example-for-calculating-confusion-matrix.mp4 (32.97 MB)
03 conditions-for-over-fitting-and-under-fitting.mp4 (14.45 MB)
04 overfitting-and-underfitting.mp4 (30.5 MB)
05 performance-metrics-mse-rmse-mae-mape.mp4 (26.41 MB)
06 r-square-rmsle-and-adjusted-r-square.mp4 (19.11 MB)
07 working-of-r-square.mp4 (23.97 MB)
08 significance-of-r-square.mp4 (29.25 MB)
01 summary-for-inception-of-machine-learning.mp4 (9.74 MB)
01 classification-in-machine-learning.mp4 (19.62 MB)
02 what-is-decision-tree.mp4 (32.56 MB)
03 decision-tree-entropy-and-information-gain.mp4 (29.62 MB)
04 step-by-step-building-of-decision-tree.mp4 (38.71 MB)
05 pruning-in-decision-tree.mp4 (26.68 MB)
06 demonstration-importing-data.mp4 (26.8 MB)
08 demonstration-importance-of-features.mp4 (14.1 MB)
09 demonstration-production-ready-random-forest.mp4 (10.99 MB)
10 demonstration-hyperparameter-tuning.mp4 (17.72 MB)
01 what-is-svm.mp4 (20.1 MB)
02 terminologies-in-svm.mp4 (42.91 MB)
03 hinge-loss-function-and-other-parameters.mp4 (43.01 MB)
04 demonstration-of-svm-exploring-the-data.mp4 (17.08 MB)
06 what-is-naive-bayes.mp4 (11.9 MB)
07 working-of-naive-bayes-bayes-theorem.mp4 (23.17 MB)
08 example-of-naive-bayes-algorithm.mp4 (37.67 MB)
09 demonstration-of-naive-bayes-code.mp4 (21.04 MB)
10 working-of-knn.mp4 (17.86 MB)
11 example-of-knn-algorithm.mp4 (23.3 MB)
12 demonstration-of-knn-setting-up-the-model.mp4 (28.2 MB)
14 demonstration-of-knn-creating-classifier.mp4 (15.24 MB)
01 dimensionality-reduction.mp4 (31.58 MB)
02 introduction-to-pca.mp4 (27.97 MB)
03 applying-pca.mp4 (23.87 MB)
04 eigen-values-and-eigen-vectors.mp4 (29.48 MB)
05 demonstration-initializing-pca.mp4 (13.78 MB)
07 demonstration-implementing-optimal-pca.mp4 (25.04 MB)
08 working-of-lda.mp4 (29.56 MB)
09 demonstration-of-lda.mp4 (32.12 MB)
01 summary-for-machine-learning-algorithms.mp4 (10.05 MB)
01 what-are-association-rules.mp4 (27.58 MB)
02 apriori-algorithm.mp4 (20.99 MB)
03 demonstrating-apriori-algorithm.mp4 (48.01 MB)
01 what-are-recommendation-engine.mp4 (22.26 MB)
02 cbf.mp4 (21.73 MB)
04 demonstration-testing-the-model.mp4 (27.23 MB)
01 course-summary-for-applied-machine-learning-with-python.mp4 (11.91 MB)
02 course-introduction.mp4 (16.72 MB)
03 environment-configuration.mp4 (11.19 MB)
01 machine-learning-vs-deep-learning.mp4 (20.38 MB)
02 what-is-deep-learning.mp4 (11.82 MB)
03 neural-networks.mp4 (24.43 MB)
04 artificial-neural-network-ann.mp4 (16.15 MB)
05 ann-types-and-applications.mp4 (11.34 MB)
06 forward-propagation.mp4 (13.19 MB)
07 perceptron.mp4 (20.54 MB)
08 learning-rate.mp4 (19.98 MB)
09 what-is-activation-function.mp4 (11.81 MB)
10 activation-function-and-its-types.mp4 (14.65 MB)
11 importance-of-epoch.mp4 (15.95 MB)
12 single-layer-perceptron-define-sigmoid-function.mp4 (25.28 MB)
13 single-layer-perceptron-decision-boundary.mp4 (42.76 MB)
01 limitations-of-single-layered-perceptron.mp4 (6.86 MB)
02 multi-layered-perceptron.mp4 (7.72 MB)
03 what-is-backpropagation.mp4 (6.49 MB)
04 backpropagation.mp4 (10.45 MB)
05 demonstration-building-a-simple-neural-network.mp4 (20.81 MB)
01 summary-of-deep-learning-components.mp4 (21.66 MB)
01 limitations-of-mlp.mp4 (16.37 MB)
03 visual-cortex-and-cnn.mp4 (20.59 MB)
04 convolutional-layer.mp4 (20.38 MB)
05 working-of-convolutional-layer.mp4 (20.38 MB)
07 demonstration-designing-the-model.mp4 (29.4 MB)
08 demonstration-building-the-cnn-model.mp4 (22.04 MB)
09 demonstration-model-accuracy.mp4 (12.09 MB)
10 demonstration-adding-more-layers.mp4 (34.12 MB)
12 demonstration-pre-trained-model.mp4 (21.2 MB)
03 tensorflow-hub.mp4 (12.52 MB)
01 summary-of-cnn-in-deep-learning.mp4 (8.47 MB)
02 summary-of-faster-rcnn.mp4 (13.77 MB)
01 rnn-fundamentals.mp4 (13.83 MB)
02 rnn-architecture.mp4 (13.94 MB)
04 implementing-rnn.mp4 (19.15 MB)
01 basics-of-lstm.mp4 (18.39 MB)
02 lstm-structure.mp4 (16.28 MB)
03 forget-gate-and-input-gate.mp4 (14.39 MB)
04 output-gate.mp4 (8.74 MB)
05 importance-of-lstm-architecture.mp4 (14.33 MB)
06 types-of-lstm.mp4 (12.05 MB)
08 demonstration-next-word-prediction-layers.mp4 (32.79 MB)
01 improving-a-model.mp4 (20.63 MB)
02 model-optimization.mp4 (13.69 MB)
03 using-adam-optimizer.mp4 (20.41 MB)
04 model-compilation.mp4 (9.68 MB)
01 course-summary-for-practical-deep-learning-with-python.mp4 (14.05 MB)
01 specialization-introduction.mp4 (16.16 MB)
03 course-introduction.mp4 (11.76 MB)
06 programming-language-and-myths.mp4 (20.15 MB)
07 python-for-ai-ml-code-simpliCity.mp4 (15.97 MB)
08 python-for-ai-ml-ease-of-learning.mp4 (15.14 MB)
09 python-tokens-types.mp4 (12.4 MB)
10 literals.mp4 (26.16 MB)
11 operators-basic-operators.mp4 (46.16 MB)
12 operators-membership-and-identity-operators.mp4 (22.48 MB)
01 explaining-data-types-in-python.mp4 (8.07 MB)
02 demonstration-of-data-types-numeric-sequence-and-mapping.mp4 (35.73 MB)
01 executing-conditional-statement.mp4 (22.98 MB)
02 demonstration-of-if-else-statement.mp4 (15.72 MB)
03 executing-while-loop.mp4 (15.38 MB)
04 demonstration-of-for-loop.mp4 (21.9 MB)
05 looping-multiple-conditions.mp4 (16.23 MB)
01 file-handling.mp4 (18.88 MB)
03 manipulating-files.mp4 (32.13 MB)
04 user-defined-functions.mp4 (30.87 MB)
05 variable-argument-and-variable-keyword-argument.mp4 (18.04 MB)
06 lambda-functions.mp4 (25.16 MB)
07 more-on-functions-and-arguments.mp4 (21.04 MB)
08 modules-in-python.mp4 (13.07 MB)
09 demonstration-of-modules.mp4 (19.7 MB)
01 summary-of-python-essentials.mp4 (7.49 MB)
02 exploring-numpy.mp4 (16.26 MB)
03 numpy-operation.mp4 (32.46 MB)
04 working-with-numpy.mp4 (35.89 MB)
02 pandas-framework.mp4 (20.7 MB)
03 pandas-dataframe-operation.mp4 (33.03 MB)
04 working-with-dataframes-in-pandas.mp4 (26.83 MB)
05 dataframes-with-pandas-operations-and-insights.mp4 (31.97 MB)
06 creating-a-series-in-pandas.mp4 (31.02 MB)
07 working-with-pandas-series.mp4 (22.04 MB)
01 dataframe-data-maniplulation.mp4 (25.83 MB)
02 dataframe-joining.mp4 (33.06 MB)
03 dataframe-grouping-the-data.mp4 (23.43 MB)
04 dataframe-data-cleaning.mp4 (22.07 MB)
05 dataframe-data-adjusting.mp4 (23.95 MB)
03 matplotlib-library.mp4 (21.62 MB)
04 plotting-charts-with-matplotlib.mp4 (19.97 MB)
05 plotting-histogram-and-box-plot.mp4 (11.14 MB)
06 plotting-multiple-charts.mp4 (29.4 MB)
07 introduction-to-seaborn-scatter-plot.mp4 (27.49 MB)
08 basic-charts-in-seaborn.mp4 (24.06 MB)
09 seaborn-heatmap-manipulation.mp4 (9.41 MB)
10 seaborn-flights-dataset.mp4 (18.83 MB)
11 seaborn-gaining-insights-in-flight-data.mp4 (23.94 MB)
12 visualizing-charts-with-plotly.mp4 (19.43 MB)
13 customizing-different-charts-in-plotly.mp4 (25.08 MB)
01 summary-exploring-numpy-and-pandas-in-python.mp4 (6.5 MB)
02 what-is-statistics.mp4 (19.13 MB)
03 measures-of-central-tendency.mp4 (22.62 MB)
04 managing-statistical-data.mp4 (22.04 MB)
05 exploring-and-analyzing-data.mp4 (14.78 MB)
01 measures-of-dispersion.mp4 (20.74 MB)
02 dispersion-demonstration.mp4 (25.14 MB)
03 application-of-dispersion-in-large-data.mp4 (8.37 MB)
02 probability-sample-space-and-events.mp4 (17.41 MB)
03 need-for-probability.mp4 (10.87 MB)
04 types-of-probability.mp4 (15.45 MB)
05 marginal-and-joint-probability-demonstration.mp4 (17.61 MB)
06 conditional-probability-demonstration.mp4 (18.8 MB)
02 what-is-hypothesis-testing.mp4 (20.23 MB)
03 steps-for-hypothesis-testing.mp4 (12.71 MB)
04 null-and-alternate-hypothesis.mp4 (20.5 MB)
05 statistical-test-interpretation.mp4 (22.22 MB)
06 one-tailed-and-two-tailed-test.mp4 (18.67 MB)
07 hypothesis-testing-demonstration.mp4 (23.02 MB)
08 margin-of-error-and-confidence-interval-demonstration.mp4 (35.07 MB)
01 summary-statistical-analysis-with-python.mp4 (7.98 MB)
01 course-summary-python-and-statistics-foundations.mp4 (10.54 MB)

]
Screenshot

Spoiler

Bitte Anmelden oder Registrieren um Code Inhalt zu sehen!

Bitte Anmelden oder Registrieren um Code Inhalt zu sehen!

Bitte Anmelden oder Registrieren um Code Inhalt zu sehen!

 

[0dayddl]

4.66 GB | 00:00:15 | mp4 | 3840X2160 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

02 course-introduction.mp4 (13.11 MB)
04 speech-recognition-technology.mp4 (17.67 MB)
05 computer-vision-application.mp4 (21.26 MB)
07 ai-responsibility-pyramid.mp4 (18.98 MB)
09 evolution-of-speech-analysis.mp4 (15.26 MB)
10 what-is-opencv.mp4 (17.82 MB)
01 installing-opencv-on-windows.mp4 (11.09 MB)
01 operations-on-opencv.mp4 (8.79 MB)
04 demonstration-gaussian-blur.mp4 (21.56 MB)
05 demonstration-edge-detection-and-conversion.mp4 (21.36 MB)
06 demonstration-image-thresholding-binary-image.mp4 (17.13 MB)
07 demonstration-different-methods-of-thresholding.mp4 (24.79 MB)
08 demonstration-practical-use-cases.mp4 (10.48 MB)
09 what-is-adaptive-thresholding.mp4 (12.3 MB)
10 demonstration-of-global-adaptive-threshold.mp4 (14.6 MB)
01 morphological-operations.mp4 (15.41 MB)
02 morphological-operations-in-opencv.mp4 (11.78 MB)
03 demonstration-opening-dilation-and-erosion.mp4 (23.22 MB)
05 blackhat-and-whitehat-transformations.mp4 (15.11 MB)
06 demonstration-whitehat-tophat.mp4 (13.87 MB)
07 demonstration-blackhat.mp4 (18.22 MB)
01 summary-of-computer-vision-with-opencv.mp4 (23.1 MB)
01 video-processing.mp4 (8.46 MB)
05 demonstration-saving-the-frames.mp4 (32.23 MB)
06 demonstration-loading-the-data.mp4 (20.23 MB)
08 demonstration-histogram-matching.mp4 (27.07 MB)
11 demonstration-differences-in-images.mp4 (15.59 MB)
01 introduction-to-speech-audio-data.mp4 (11.02 MB)
03 processing-speech.mp4 (18.26 MB)
04 speech-production.mp4 (20.63 MB)
05 difficulties-in-analyzing-speech.mp4 (17.91 MB)
06 working-of-sound-waves.mp4 (14.68 MB)
07 adc-and-sample-rate-bit-rate.mp4 (12.01 MB)
09 demonstration-generating-sound.mp4 (33.68 MB)
10 demonstration-spectrogram.mp4 (27.63 MB)
12 summary-of-audio-file-analysis.mp4 (7.38 MB)
01 human-speech.mp4 (18.91 MB)
02 speech-waveform.mp4 (18.02 MB)
03 digital-signal-processing.mp4 (18.18 MB)
11 tremor-detection.mp4 (6.51 MB)
01 Traffic.mp4 (185.81 MB)
01 highway.mp4 (4.98 MB)
02 course-introduction.mp4 (14.8 MB)
03 machine-learning-in-industry.mp4 (15.59 MB)
04 how-companies-use-machine-learning.mp4 (18.89 MB)
01 machine-learning-process.mp4 (14.84 MB)
02 steps-in-machine-learning.mp4 (13.79 MB)
03 types-of-machine-learning.mp4 (21.81 MB)
01 introduction-to-linear-regression.mp4 (18.61 MB)
02 real-life-examples.mp4 (22.05 MB)
03 calculating-ols.mp4 (40.38 MB)
04 equation-of-ols.mp4 (16.29 MB)
05 assumptions-in-linear-regression.mp4 (22.41 MB)
06 demonstration-setting-up-the-model.mp4 (23.13 MB)
07 calculating-r-square-and-rmse.mp4 (28.36 MB)
08 residual-plot-and-q-q-plot.mp4 (9.96 MB)
09 cooks-distance.mp4 (22.59 MB)
10 real-life-examples-of-logistic-regression.mp4 (21.03 MB)
11 what-is-logistic-regression.mp4 (26.84 MB)
12 cost-function.mp4 (13.93 MB)
13 assumptions-in-logistic-regression.mp4 (19.09 MB)
14 demonstration-of-logistic-regression-transforming-data.mp4 (29.9 MB)
15 demonstration-of-logistic-regression-developing-the-model.mp4 (18.35 MB)
01 confusion-matrix.mp4 (12.22 MB)
02 example-for-calculating-confusion-matrix.mp4 (32.97 MB)
03 conditions-for-over-fitting-and-under-fitting.mp4 (14.45 MB)
04 overfitting-and-underfitting.mp4 (30.5 MB)
05 performance-metrics-mse-rmse-mae-mape.mp4 (26.41 MB)
06 r-square-rmsle-and-adjusted-r-square.mp4 (19.11 MB)
07 working-of-r-square.mp4 (23.97 MB)
08 significance-of-r-square.mp4 (29.25 MB)
01 summary-for-inception-of-machine-learning.mp4 (9.74 MB)
01 classification-in-machine-learning.mp4 (19.62 MB)
02 what-is-decision-tree.mp4 (32.56 MB)
03 decision-tree-entropy-and-information-gain.mp4 (29.62 MB)
04 step-by-step-building-of-decision-tree.mp4 (38.71 MB)
05 pruning-in-decision-tree.mp4 (26.68 MB)
06 demonstration-importing-data.mp4 (26.8 MB)
08 demonstration-importance-of-features.mp4 (14.1 MB)
09 demonstration-production-ready-random-forest.mp4 (10.99 MB)
10 demonstration-hyperparameter-tuning.mp4 (17.72 MB)
01 what-is-svm.mp4 (20.1 MB)
02 terminologies-in-svm.mp4 (42.91 MB)
03 hinge-loss-function-and-other-parameters.mp4 (43.01 MB)
04 demonstration-of-svm-exploring-the-data.mp4 (17.08 MB)
06 what-is-naive-bayes.mp4 (11.9 MB)
07 working-of-naive-bayes-bayes-theorem.mp4 (23.17 MB)
08 example-of-naive-bayes-algorithm.mp4 (37.67 MB)
09 demonstration-of-naive-bayes-code.mp4 (21.04 MB)
10 working-of-knn.mp4 (17.86 MB)
11 example-of-knn-algorithm.mp4 (23.3 MB)
12 demonstration-of-knn-setting-up-the-model.mp4 (28.2 MB)
14 demonstration-of-knn-creating-classifier.mp4 (15.24 MB)
01 dimensionality-reduction.mp4 (31.58 MB)
02 introduction-to-pca.mp4 (27.97 MB)
03 applying-pca.mp4 (23.87 MB)
04 eigen-values-and-eigen-vectors.mp4 (29.48 MB)
05 demonstration-initializing-pca.mp4 (13.78 MB)
07 demonstration-implementing-optimal-pca.mp4 (25.04 MB)
08 working-of-lda.mp4 (29.56 MB)
09 demonstration-of-lda.mp4 (32.12 MB)
01 summary-for-machine-learning-algorithms.mp4 (10.05 MB)
01 what-are-association-rules.mp4 (27.58 MB)
02 apriori-algorithm.mp4 (20.99 MB)
03 demonstrating-apriori-algorithm.mp4 (48.01 MB)
01 what-are-recommendation-engine.mp4 (22.26 MB)
02 cbf.mp4 (21.73 MB)
04 demonstration-testing-the-model.mp4 (27.23 MB)
01 course-summary-for-applied-machine-learning-with-python.mp4 (11.91 MB)
02 course-introduction.mp4 (16.72 MB)
03 environment-configuration.mp4 (11.19 MB)
01 machine-learning-vs-deep-learning.mp4 (20.38 MB)
02 what-is-deep-learning.mp4 (11.82 MB)
03 neural-networks.mp4 (24.43 MB)
04 artificial-neural-network-ann.mp4 (16.15 MB)
05 ann-types-and-applications.mp4 (11.34 MB)
06 forward-propagation.mp4 (13.19 MB)
07 perceptron.mp4 (20.54 MB)
08 learning-rate.mp4 (19.98 MB)
09 what-is-activation-function.mp4 (11.81 MB)
10 activation-function-and-its-types.mp4 (14.65 MB)
11 importance-of-epoch.mp4 (15.95 MB)
12 single-layer-perceptron-define-sigmoid-function.mp4 (25.28 MB)
13 single-layer-perceptron-decision-boundary.mp4 (42.76 MB)
01 limitations-of-single-layered-perceptron.mp4 (6.86 MB)
02 multi-layered-perceptron.mp4 (7.72 MB)
03 what-is-backpropagation.mp4 (6.49 MB)
04 backpropagation.mp4 (10.45 MB)
05 demonstration-building-a-simple-neural-network.mp4 (20.81 MB)
01 summary-of-deep-learning-components.mp4 (21.66 MB)
01 limitations-of-mlp.mp4 (16.37 MB)
03 visual-cortex-and-cnn.mp4 (20.59 MB)
04 convolutional-layer.mp4 (20.38 MB)
05 working-of-convolutional-layer.mp4 (20.38 MB)
07 demonstration-designing-the-model.mp4 (29.4 MB)
08 demonstration-building-the-cnn-model.mp4 (22.04 MB)
09 demonstration-model-accuracy.mp4 (12.09 MB)
10 demonstration-adding-more-layers.mp4 (34.12 MB)
12 demonstration-pre-trained-model.mp4 (21.2 MB)
03 tensorflow-hub.mp4 (12.52 MB)
01 summary-of-cnn-in-deep-learning.mp4 (8.47 MB)
02 summary-of-faster-rcnn.mp4 (13.77 MB)
01 rnn-fundamentals.mp4 (13.83 MB)
02 rnn-architecture.mp4 (13.94 MB)
04 implementing-rnn.mp4 (19.15 MB)
01 basics-of-lstm.mp4 (18.39 MB)
02 lstm-structure.mp4 (16.28 MB)
03 forget-gate-and-input-gate.mp4 (14.39 MB)
04 output-gate.mp4 (8.74 MB)
05 importance-of-lstm-architecture.mp4 (14.33 MB)
06 types-of-lstm.mp4 (12.05 MB)
08 demonstration-next-word-prediction-layers.mp4 (32.79 MB)
01 improving-a-model.mp4 (20.63 MB)
02 model-optimization.mp4 (13.69 MB)
03 using-adam-optimizer.mp4 (20.41 MB)
04 model-compilation.mp4 (9.68 MB)
01 course-summary-for-practical-deep-learning-with-python.mp4 (14.05 MB)
01 specialization-introduction.mp4 (16.16 MB)
03 course-introduction.mp4 (11.76 MB)
06 programming-language-and-myths.mp4 (20.15 MB)
07 python-for-ai-ml-code-simpliCity.mp4 (15.97 MB)
08 python-for-ai-ml-ease-of-learning.mp4 (15.14 MB)
09 python-tokens-types.mp4 (12.4 MB)
10 literals.mp4 (26.16 MB)
11 operators-basic-operators.mp4 (46.16 MB)
12 operators-membership-and-identity-operators.mp4 (22.48 MB)
01 explaining-data-types-in-python.mp4 (8.07 MB)
02 demonstration-of-data-types-numeric-sequence-and-mapping.mp4 (35.73 MB)
01 executing-conditional-statement.mp4 (22.98 MB)
02 demonstration-of-if-else-statement.mp4 (15.72 MB)
03 executing-while-loop.mp4 (15.38 MB)
04 demonstration-of-for-loop.mp4 (21.9 MB)
05 looping-multiple-conditions.mp4 (16.23 MB)
01 file-handling.mp4 (18.88 MB)
03 manipulating-files.mp4 (32.13 MB)
04 user-defined-functions.mp4 (30.87 MB)
05 variable-argument-and-variable-keyword-argument.mp4 (18.04 MB)
06 lambda-functions.mp4 (25.16 MB)
07 more-on-functions-and-arguments.mp4 (21.04 MB)
08 modules-in-python.mp4 (13.07 MB)
09 demonstration-of-modules.mp4 (19.7 MB)
01 summary-of-python-essentials.mp4 (7.49 MB)
02 exploring-numpy.mp4 (16.26 MB)
03 numpy-operation.mp4 (32.46 MB)
04 working-with-numpy.mp4 (35.89 MB)
02 pandas-framework.mp4 (20.7 MB)
03 pandas-dataframe-operation.mp4 (33.03 MB)
04 working-with-dataframes-in-pandas.mp4 (26.83 MB)
05 dataframes-with-pandas-operations-and-insights.mp4 (31.97 MB)
06 creating-a-series-in-pandas.mp4 (31.02 MB)
07 working-with-pandas-series.mp4 (22.04 MB)
01 dataframe-data-maniplulation.mp4 (25.83 MB)
02 dataframe-joining.mp4 (33.06 MB)
03 dataframe-grouping-the-data.mp4 (23.43 MB)
04 dataframe-data-cleaning.mp4 (22.07 MB)
05 dataframe-data-adjusting.mp4 (23.95 MB)
03 matplotlib-library.mp4 (21.62 MB)
04 plotting-charts-with-matplotlib.mp4 (19.97 MB)
05 plotting-histogram-and-box-plot.mp4 (11.14 MB)
06 plotting-multiple-charts.mp4 (29.4 MB)
07 introduction-to-seaborn-scatter-plot.mp4 (27.49 MB)
08 basic-charts-in-seaborn.mp4 (24.06 MB)
09 seaborn-heatmap-manipulation.mp4 (9.41 MB)
10 seaborn-flights-dataset.mp4 (18.83 MB)
11 seaborn-gaining-insights-in-flight-data.mp4 (23.94 MB)
12 visualizing-charts-with-plotly.mp4 (19.43 MB)
13 customizing-different-charts-in-plotly.mp4 (25.08 MB)
01 summary-exploring-numpy-and-pandas-in-python.mp4 (6.5 MB)
02 what-is-statistics.mp4 (19.13 MB)
03 measures-of-central-tendency.mp4 (22.62 MB)
04 managing-statistical-data.mp4 (22.04 MB)
05 exploring-and-analyzing-data.mp4 (14.78 MB)
01 measures-of-dispersion.mp4 (20.74 MB)
02 dispersion-demonstration.mp4 (25.14 MB)
03 application-of-dispersion-in-large-data.mp4 (8.37 MB)
02 probability-sample-space-and-events.mp4 (17.41 MB)
03 need-for-probability.mp4 (10.87 MB)
04 types-of-probability.mp4 (15.45 MB)
05 marginal-and-joint-probability-demonstration.mp4 (17.61 MB)
06 conditional-probability-demonstration.mp4 (18.8 MB)
02 what-is-hypothesis-testing.mp4 (20.23 MB)
03 steps-for-hypothesis-testing.mp4 (12.71 MB)
04 null-and-alternate-hypothesis.mp4 (20.5 MB)
05 statistical-test-interpretation.mp4 (22.22 MB)
06 one-tailed-and-two-tailed-test.mp4 (18.67 MB)
07 hypothesis-testing-demonstration.mp4 (23.02 MB)
08 margin-of-error-and-confidence-interval-demonstration.mp4 (35.07 MB)
01 summary-statistical-analysis-with-python.mp4 (7.98 MB)
01 course-summary-python-and-statistics-foundations.mp4 (10.54 MB)

]
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