Learn Python for Data Science Machine Learning from AZ | 1CB7699A3BD48B6490C822017633266B1B1F008D

Learn Python for Data Science Machine Learning from AZ

Name	Learn Python for Data Science & Machine Learning from AZ	DOWNLOAD Copy Link
Total Size	8.0 GB
Total Files	457
Last Seen	2024-10-06 23:58
Hash	1CB7699A3BD48B6490C822017633266B1B1F008D

/19 - PCA/
127 - PCA Image Compression.mp4	262.1 MB
122 - What is PCA English.vtt	12.7 KB
125 - SVD details.txt	0.1 KB
127 - cat.png	123.1 KB
127 - Compression Ratio.txt	0.1 KB
129 - PCA Biplot and the Screen Plot.mp4	142.2 MB
127 - PCA Image Compression English.vtt	34.3 KB
129 - PCA Biplot and the Screen Plot English.vtt	22.8 KB
128 - PCA Data Preprocessing English.vtt	18.3 KB
124 - PCA Algorithm Steps Mathematics English.vtt	16.2 KB
124 - Linear Algebra Refresher.txt	0.0 KB
124 - Principal components eigenvectors.txt	0.0 KB
130 - PCA Feature Scaling and Screen Plot English.vtt	12.6 KB
132 - PCA Visualization English.vtt	9.6 KB
128 - PCA Data Preprocessing.mp4	126.3 MB
131 - PCA Supervised vs Unsupervised English.vtt	6.3 KB
121 - PCA Section Overview English.vtt	6.3 KB
125 - Covariance Matrix vs SVD English.vtt	5.9 KB
123 - PCA Drawbacks English.vtt	4.4 KB
126 - PCA Main Applications English.vtt	3.5 KB
129 - USArrests.csv	1.3 KB
130 - PCA Feature Scaling and Screen Plot.mp4	71.5 MB
132 - PCA Visualization.mp4	71.3 MB
124 - PCA Algorithm Steps Mathematics.mp4	60.5 MB
122 - What is PCA.mp4	49.6 MB
125 - Covariance Matrix vs SVD.mp4	40.6 MB
131 - PCA Supervised vs Unsupervised.mp4	37.5 MB
121 - PCA Section Overview.mp4	33.3 MB
123 - PCA Drawbacks.mp4	20.4 MB
126 - PCA Main Applications.mp4	10.5 MB
121 - PCAipynb	3.4 MB
/
TutsNode.net.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/.../6 - NumPy Data Analysis/
45 - NumPyBasics.pdf	79.0 KB
47 - NumPy Arrays Basics English.vtt	15.1 KB
45 - Intro NumPy Array Data Types English.vtt	16.5 KB
48 - NumPy Array Indexing English.vtt	12.6 KB
46 - NumPy Arrays English.vtt	10.0 KB
49 - NumPy Array Computations English.vtt	7.7 KB
50 - Broadcasting English.vtt	5.7 KB
47 - NumPy Arrays Basics.mp4	41.9 MB
48 - NumPy Array Indexing.mp4	36.4 MB
45 - Intro NumPy Array Data Types.mp4	36.4 MB
46 - NumPy Arrays.mp4	33.9 MB
50 - Broadcasting.mp4	18.7 MB
49 - NumPy Array Computations.mp4	17.8 MB
/.../15 - Decision Trees/
80 - Adult Dataset.txt	0.0 KB
86 - Evaluating our ID3 implementation English.vtt	21.3 KB
85 - ID3 Putting Everything Together.mp4	191.3 MB
81 - What is Entropy and Information Gain.mp4	142.7 MB
87 - Passing categorical data to Sklearn Decision Tree.txt	0.1 KB
85 - ID3 Putting Everything Together English.vtt	26.8 KB
81 - What is Entropy and Information Gain English.vtt	25.6 KB
79 - DecisionTreesipynb	797.3 KB
87 - Categorical feature in Treebased classifiers.txt	0.1 KB
91 - Pruning English.vtt	21.1 KB
80 - EDA on Adult Dataset English.vtt	20.8 KB
90 - Decision Trees Hyperparameters English.vtt	14.2 KB
82 - The Decision Tree ID3 algorithm from scratch Part 1 English.vtt	13.1 KB
88 - Visualizing the tree English.vtt	13.0 KB
79 - Decision Trees Section Overview English.vtt	5.1 KB
80 - EDA on Adult Dataset.mp4	129.2 MB
87 - Compare with Sklearn implementation English.vtt	10.8 KB
86 - Evaluating our ID3 implementation.mp4	127.9 MB
83 - The Decision Tree ID3 algorithm from scratch Part 2 English.vtt	9.4 KB
93 - Decision Trees Pros and Cons English.vtt	9.4 KB
89 - Plot the features importance English.vtt	6.9 KB
80 - adultnames.csv	5.2 KB
84 - The Decision Tree ID3 algorithm from scratch Part 3 English.vtt	5.1 KB
92 - Optional Gain Ration English.vtt	3.3 KB
94 - Project Predict whether income exceeds 50Kyr Overview English.vtt	3.2 KB
91 - Pruning.mp4	118.5 MB
82 - The Decision Tree ID3 algorithm from scratch Part 1.mp4	89.4 MB
90 - Decision Trees Hyperparameters.mp4	85.2 MB
88 - Visualizing the tree.mp4	71.5 MB
87 - Compare with Sklearn implementation.mp4	68.8 MB
83 - The Decision Tree ID3 algorithm from scratch Part 2.mp4	67.1 MB
93 - Decision Trees Pros and Cons.mp4	50.1 MB
84 - The Decision Tree ID3 algorithm from scratch Part 3.mp4	35.0 MB
89 - Plot the features importance.mp4	33.2 MB
92 - Optional Gain Ration.mp4	20.1 MB
79 - Decision Trees Section Overview.mp4	17.2 MB
94 - Project Predict whether income exceeds 50Kyr Overview.mp4	15.8 MB
80 - adultdata.csv	4.0 MB
80 - adulttest.csv	2.0 MB
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133	124.0 KB
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138	263.3 KB
139	220.0 KB
140	758.4 KB
/.../16 - Ensemble Learning and Random Forests/
100 - Implementing Random Forests from scratch Part 1.mp4	212.4 MB
95 - EnsembleLearningipynb	36.6 KB
96 - Ensemble Learning Example.txt	0.1 KB
100 - Implementing Random Forests from scratch Part 1 English.vtt	26.3 KB
107 - AdaBoost Part 2 English.vtt	18.1 KB
96 - What is Ensemble Learning English.vtt	15.5 KB
97 - What is Bootstrap Sampling English.vtt	9.7 KB
99 - OutofBag Error OOB Error English.vtt	8.8 KB
101 - Implementing Random Forests from scratch Part 2 English.vtt	7.3 KB
104 - Random Forests Pros and Cons English.vtt	6.9 KB
98 - What is Bagging English.vtt	6.8 KB
105 - What is Boosting English.vtt	6.0 KB
103 - Random Forests HyperParameters English.vtt	5.3 KB
106 - AdaBoost Part 1 English.vtt	4.8 KB
95 - Ensemble Learning Section Overview English.vtt	4.7 KB
102 - Compare with sklearn implementation English.vtt	4.5 KB
96 - What is Ensemble Learning.mp4	96.4 MB
107 - AdaBoost Part 2.mp4	90.1 MB
97 - What is Bootstrap Sampling.mp4	58.6 MB
101 - Implementing Random Forests from scratch Part 2.mp4	53.0 MB
99 - OutofBag Error OOB Error.mp4	44.1 MB
103 - Random Forests HyperParameters.mp4	41.6 MB
105 - What is Boosting.mp4	37.2 MB
98 - What is Bagging.mp4	30.9 MB
102 - Compare with sklearn implementation.mp4	29.0 MB
106 - AdaBoost Part 1.mp4	26.8 MB
104 - Random Forests Pros and Cons.mp4	20.6 MB
95 - Ensemble Learning Section Overview.mp4	16.9 MB
/.../14 - K Nearest Neighbors/
66 - KNNipynb	333.1 KB
68 - EDA on Iris Dataset English.vtt	28.0 KB
68 - EDA on Iris Dataset.mp4	169.7 MB
68 - Sklearn Toy Datasets.txt	0.1 KB
74 - MIT example.txt	0.1 KB
73 - Stanford Demo KNN Decision Boundary.txt	0.1 KB
70 - Implement the KNN algorithm from scratch English.vtt	14.9 KB
74 - Manhattan vs Euclidean Distance English.vtt	13.9 KB
72 - Hyperparameter tuning using the crossvalidation English.vtt	12.9 KB
69 - The KNN Intuition English.vtt	2.7 KB
76 - Curse of dimensionality English.vtt	8.5 KB
75 - Feature scaling in KNN English.vtt	7.1 KB
78 - KNN pros and cons English.vtt	6.9 KB
73 - The decision boundary visualization English.vtt	6.3 KB
71 - Compare the result with the sklearn library English.vtt	4.6 KB
77 - KNN use cases English.vtt	4.3 KB
67 - parametric vs nonparametric models English.vtt	4.2 KB
66 - KNN Overview English.vtt	3.9 KB
72 - Hyperparameter tuning using the crossvalidation.mp4	94.7 MB
70 - Implement the KNN algorithm from scratch.mp4	91.2 MB
74 - Manhattan vs Euclidean Distance.mp4	80.1 MB
75 - Feature scaling in KNN.mp4	51.8 MB
76 - Curse of dimensionality.mp4	48.2 MB
78 - KNN pros and cons.mp4	31.9 MB
77 - KNN use cases.mp4	30.3 MB
71 - Compare the result with the sklearn library.mp4	25.8 MB
73 - The decision boundary visualization.mp4	17.7 MB
67 - parametric vs nonparametric models.mp4	16.4 MB
66 - KNN Overview.mp4	13.5 MB
69 - The KNN Intuition.mp4	8.5 MB
/.../3 - Python For Data Science/
15 - PythonBasics.pdf	130.8 KB
27 - Is it possible to have autocomplete in a notebook in Google Colab.txt	0.1 KB
16 - JupyterNotebook.pdf	314.5 KB
15 - ImportingPythonData.pdf	63.0 KB
18 - Python Variables Booleans and None English.vtt	13.4 KB
28 - Python Official Docs on Dictionaries.txt	0.1 KB
20 - Python Operators English.vtt	27.6 KB
28 - Python Dictionaries English.vtt	24.3 KB
32 - Object Oriented Programming in Python English.vtt	22.7 KB
31 - Python Functions English.vtt	18.5 KB
26 - More about Lists English.vtt	17.7 KB
23 - Python Conditional Statements English.vtt	16.2 KB
30 - Compound Data Types & When to use each one English.vtt	15.7 KB
22 - Python Strings English.vtt	14.4 KB
27 - Python Tuples English.vtt	13.1 KB
29 - Python Sets English.vtt	11.8 KB
19 - Getting Started with Google Colab English.vtt	11.0 KB
24 - Python For Loops and While Loops English.vtt	9.6 KB
21 - Python Numbers & Booleans English.vtt	8.6 KB
14 - What is Programming English.vtt	8.1 KB
25 - Python Lists English.vtt	6.4 KB
15 - Why Python for Data Science English.vtt	6.1 KB
16 - What is Jupyter English.vtt	5.3 KB
17 - What is Google Colab English.vtt	4.5 KB
28 - Python Dictionaries.mp4	109.2 MB
20 - Python Operators.mp4	91.0 MB
32 - Object Oriented Programming in Python.mp4	73.7 MB
31 - Python Functions.mp4	65.5 MB
26 - More about Lists.mp4	63.3 MB
22 - Python Strings.mp4	59.0 MB
23 - Python Conditional Statements.mp4	57.3 MB
27 - Python Tuples.mp4	57.2 MB
30 - Compound Data Types & When to use each one.mp4	49.3 MB
18 - Python Variables Booleans and None.mp4	40.1 MB
19 - Getting Started with Google Colab.mp4	36.8 MB
29 - Python Sets.mp4	30.9 MB
21 - Python Numbers & Booleans.mp4	26.8 MB
24 - Python For Loops and While Loops.mp4	26.8 MB
25 - Python Lists.mp4	22.5 MB
14 - What is Programming.mp4	19.2 MB
15 - Why Python for Data Science.mp4	17.1 MB
16 - What is Jupyter.mp4	15.3 MB
17 - What is Google Colab.mp4	8.6 MB
/.../7 - Pandas Data Analysis/
51 - PandasBasics.pdf	78.9 KB
51 - Pandas.pdf	112.8 KB
52 - Introduction to Pandas Continued English.vtt	24.0 KB
51 - Introduction to Pandas English.vtt	20.0 KB
52 - Introduction to Pandas Continued.mp4	74.5 MB
51 - Introduction to Pandas.mp4	49.1 MB
/.../5 - Probability & Hypothesis Testing/
42 - Expected Values English.vtt	3.6 KB
44 - Hypothesis Testing Overview English.vtt	12.8 KB
43 - Relative Frequency English.vtt	7.5 KB
41 - What Exactly is Probability English.vtt	5.8 KB
44 - Hypothesis Testing Overview.mp4	63.5 MB
43 - Relative Frequency.mp4	34.3 MB
41 - What Exactly is Probability.mp4	28.5 MB
42 - Expected Values.mp4	15.4 MB
/18 - Kmeans/
118 - Unsupervised Machine Learning Intro English.vtt	26.4 KB
119 - Unsupervised Machine Learning Continued English.vtt	26.1 KB
120 - Data Standardization English.vtt	25.3 KB
118 - UnsupervisedLearning.pdf	651.8 KB
120 - Data Standardization.mp4	114.9 MB
118 - Unsupervised Machine Learning Intro.mp4	105.8 MB
119 - Unsupervised Machine Learning Continued.mp4	87.2 MB
/9 - Machine Learning/
56 - SupervisedLearning.pdf	856.8 KB
56 - Introduction To Machine Learning English.vtt	33.1 KB
56 - Introduction To Machine Learning.mp4	103.5 MB
/.../13 - Linear and Logistic Regression/
63 - Linear Regression Correlation Methods English.vtt	34.5 KB
61 - Linear Regression Intro English.vtt	11.0 KB
62 - Gradient Descent English.vtt	7.6 KB
64 - Linear Regression Implementation English.vtt	6.2 KB
65 - Logistic Regression English.vtt	4.4 KB
63 - Linear Regression Correlation Methods.mp4	115.7 MB
61 - Linear Regression Intro.mp4	32.3 MB
64 - Linear Regression Implementation.mp4	18.7 MB
62 - Gradient Descent.mp4	16.7 MB
65 - Logistic Regression.mp4	9.3 MB
/.../8 - Python Data Visualization/
53 - Data Visualization Overview English.vtt	32.8 KB
54 - Different Data Visualization Libraries in Python English.vtt	16.5 KB
55 - Python Data Visualization Implementation English.vtt	11.2 KB
53 - Data Visualization Overview.mp4	76.6 MB
54 - Different Data Visualization Libraries in Python.mp4	43.1 MB
55 - Python Data Visualization Implementation.mp4	28.8 MB
/1 - Introduction/
6 - How To Get a Data Science Job English.vtt	27.1 KB
5 - What is a Data Scientist English.vtt	23.8 KB
6 - How To Get a Data Science Job.mp4	137.6 MB
5 - What is a Data Scientist.mp4	133.6 MB
7 - Data Science Projects Overview English.vtt	16.9 KB
4 - Data Science Job Roles English.vtt	14.0 KB
2 - Data Science Machine Learning Marketplace English.vtt	9.3 KB
3 - Data Science Job Opportunities English.vtt	6.2 KB
1 - Who is This Course For English.vtt	3.6 KB
4 - Data Science Job Roles.mp4	83.7 MB
7 - Data Science Projects Overview.mp4	83.3 MB
2 - Data Science Machine Learning Marketplace.mp4	49.2 MB
3 - Data Science Job Opportunities.mp4	30.8 MB
1 - Who is This Course For.mp4	18.0 MB
/.../17 - Support Vector Machines/
113 - SVM Kernel Types English.vtt	23.1 KB
117 - Kaggle Gender Recognition by Voice and Speech Analysis.txt	0.0 KB
113 - SVM RBF Visualization.txt	0.0 KB
113 - SVM with polynomial kernel visualization.txt	0.0 KB
114 - SVM with Linear Dataset Iris English.vtt	17.3 KB
110 - Hard vs Soft Margins English.vtt	16.4 KB
115 - SVM with Nonlinear Dataset English.vtt	15.9 KB
112 - Kernel Trick English.vtt	15.8 KB
109 - SVM intuition English.vtt	13.9 KB
113 - SVM Kernel Types.mp4	132.5 MB
108 - SVMipynb	652.7 KB
108 - SVM Outline English.vtt	6.5 KB
116 - SVM with Regression English.vtt	7.1 KB
117 - Project Voice Gender Recognition using SVM English.vtt	5.5 KB
111 - C hyperparameter English.vtt	4.9 KB
115 - SVM with Nonlinear Dataset.mp4	117.0 MB
114 - SVM with Linear Dataset Iris.mp4	106.5 MB
112 - Kernel Trick.mp4	80.8 MB
110 - Hard vs Soft Margins.mp4	68.8 MB
109 - SVM intuition.mp4	51.2 MB
117 - Project Voice Gender Recognition using SVM.mp4	41.5 MB
108 - SVM Outline.mp4	37.0 MB
116 - SVM with Regression.mp4	26.2 MB
111 - C hyperparameter.mp4	22.1 MB
/.../11 - Data Cleaning/
58 - Feature Scaling English.vtt	10.5 KB
59 - Data Cleaning English.vtt	10.4 KB
59 - Data Cleaning.mp4	31.7 MB
58 - Feature Scaling.mp4	20.3 MB
/.../2 - Data Science & Machine Learning Concepts/
11 - Machine Learning Concepts & Algorithms English.vtt	20.7 KB
10 - What is Machine Learning English.vtt	20.1 KB
9 - What is Data Science English.vtt	18.8 KB
13 - Machine Learning vs Deep Learning English.vtt	15.8 KB
12 - What is Deep Learning English.vtt	13.9 KB
8 - Why We Use Python English.vtt	4.3 KB
9 - What is Data Science.mp4	92.3 MB
10 - What is Machine Learning.mp4	87.5 MB
11 - Machine Learning Concepts & Algorithms.mp4	81.8 MB
12 - What is Deep Learning.mp4	81.6 MB
13 - Machine Learning vs Deep Learning.mp4	79.6 MB
8 - Why We Use Python.mp4	14.2 MB
/.../4 - Statistics for Data Science/
38 - Inferential Statistics English.vtt	19.9 KB
39 - Measure of Asymmetry English.vtt	2.5 KB
35 - Measure of Variability English.vtt	16.2 KB
36 - Measure of Variability Continued English.vtt	12.0 KB
33 - Intro To Statistics English.vtt	10.0 KB
37 - Measures of Variable Relationship English.vtt	9.8 KB
40 - Sampling Distribution English.vtt	9.3 KB
34 - Descriptive Statistics English.vtt	9.0 KB
38 - Inferential Statistics.mp4	47.2 MB
35 - Measure of Variability.mp4	40.1 MB
36 - Measure of Variability Continued.mp4	36.3 MB
40 - Sampling Distribution.mp4	27.7 MB
37 - Measures of Variable Relationship.mp4	24.7 MB
34 - Descriptive Statistics.mp4	22.5 MB
33 - Intro To Statistics.mp4	22.3 MB
39 - Measure of Asymmetry.mp4	7.1 MB
/.../10 - Data Loading & Exploration/
57 - Exploratory Data Analysis English.vtt	17.2 KB
57 - Exploratory Data Analysis.mp4	53.0 MB
/.../20 - Data Science Career/
133 - Creating A Data Science Resume English.vtt	9.4 KB
137 - Top Freelance Websites English.vtt	7.5 KB
135 - How to Contact Recruiters English.vtt	6.5 KB
136 - Getting Started with Freelancing English.vtt	6.3 KB
138 - Personal Branding English.vtt	5.7 KB
139 - Networking Dos and Donts English.vtt	5.5 KB
134 - Data Science Cover Letter English.vtt	5.3 KB
140 - Importance of a Website English.vtt	4.2 KB
133 - Creating A Data Science Resume.mp4	38.9 MB
138 - Personal Branding.mp4	32.0 MB
136 - Getting Started with Freelancing.mp4	31.7 MB
137 - Top Freelance Websites.mp4	31.0 MB
135 - How to Contact Recruiters.mp4	25.8 MB
139 - Networking Dos and Donts.mp4	24.8 MB
134 - Data Science Cover Letter.mp4	24.1 MB
140 - Importance of a Website.mp4	16.1 MB
/.../12 - Feature Selecting and Engineering/
60 - Feature Engineering English.vtt	8.5 KB
60 - Feature Engineering.mp4	19.3 MB
Total files 457