Master Machine Learning And AI with Python

2.46 GB | 10min 45s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English

Files Included :
1 -What is Machine Learning.mp4 (34.1 MB)
2 -Types of Machine Learning.mp4 (31.58 MB)
3 -Applications of Machine Learning.mp4 (66.39 MB)
4 -Tools and Libraries for Machine Learning.mp4 (65.51 MB)
1 -K-means Clustering.mp4 (46.75 MB)
2 -Hierarchical Clustering.mp4 (49.98 MB)
3 -Density-based Spatial Clustering.mp4 (48.36 MB)
4 -Gaussian Mixture Models.mp4 (67.84 MB)
1 -Introduction of Association Rule Learning.mp4 (30.58 MB)
2 -Apriori Algorithm.mp4 (51.83 MB)
3 -Eclat Algorithm.mp4 (46.49 MB)
1 -Introduction of Natural Laungage Processing (NLP).mp4 (60.83 MB)
2 -Text Preprocessing Techniques.mp4 (19.8 MB)
3 -Tokenization - Text Preprocessing.mp4 (9.09 MB)
4 -Stopword Removal - Text Preprocessing.mp4 (13.37 MB)
5 -Stemming and Lemmazation - Text Preprocessing.mp4 (18.02 MB)
6 -Bag of Words Model.mp4 (42.85 MB)
7 -Understanding TF-IDF.mp4 (54.32 MB)
8 -Sentiment Analysis.mp4 (52.87 MB)
1 -Introduction of Deep Learning.mp4 (43.84 MB)
2 -Building Neural Networks.mp4 (25.02 MB)
3 -Training Neural Networks.mp4 (55.64 MB)
4 -cnn.zip (1.66 KB)
4 -Convolutional Neural Networks(CNNs).mp4 (58.85 MB)
5 -Recurrent Neural Networks(RNNs).mp4 (60.86 MB)
6 -Keras and Tensorflow.mp4 (67.86 MB)
1 -Data Preprocessing in Machine Learning.mp4 (23.13 MB)
2 -datastructure.zip (1.54 KB)
2 -Working with Structured Data.mp4 (27.34 MB)
3 -Data Exploration.mp4 (43.4 MB)
4 -Data Visualization without Libraries.mp4 (35.08 MB)
1 -Handling Missing Data.mp4 (90.58 MB)
1 -handlingMissingData.zip (1.91 KB)
1 -Introduction.mp4 (13.99 MB)
2 -Label Encoding.mp4 (23.69 MB)
3 -One-Hot Encoding.mp4 (29.74 MB)
4 -Encoding Techniques for High Cardinality.mp4 (4.86 MB)
5 -Target Encoding.mp4 (27.12 MB)
6 -Frequency Encoding.mp4 (28.69 MB)
7 -Hash Encoding.mp4 (33.74 MB)
8 -Key Insight.mp4 (18.04 MB)
1 -Feature Scaling.mp4 (50.31 MB)
1 -introduction Feature Engineering.mp4 (28.71 MB)
2 -Filter Methods.mp4 (37.02 MB)
3 -Wrapper Methods.mp4 (16.97 MB)
4 -Embedded Methods.mp4 (15.74 MB)
1 -Data Splitting Techniques.mp4 (4.83 MB)
2 -Training and Testing sets.mp4 (19.35 MB)
3 -Cross-validation techniques.mp4 (21.5 MB)
1 -Introduction of Regression.mp4 (26.84 MB)
2 -Simple Linear Regression.mp4 (39.38 MB)
3 -Multiple Linear Regression.mp4 (55.8 MB)
4 -Polynomial Regression.mp4 (33.18 MB)
5 -Support Vector Regression (SVR).mp4 (59.46 MB)
6 -Decision Tree Regression.mp4 (67.07 MB)
7 -Random Forest Regression.mp4 (69.72 MB)
1 -Introduction of Classification Techniques.mp4 (25.68 MB)
2 -Binary Logistic Regression.mp4 (31.67 MB)
3 -Multiclass Logistic Regression.mp4 (29.77 MB)
4 -K-Nearest Neighbors.mp4 (46.53 MB)
5 -Support Vector Machines.mp4 (42.15 MB)
6 -Naive Bayes.mp4 (65.53 MB)
7 -Decision Trees For Classification.mp4 (60.22 MB)
8 -Random Forest.mp4 (67.04 MB)
9 -Boosting Algorithms.mp4 (87.4 MB)
9 -boostingAlgorithm.zip (2.9 KB)]
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