2021 Python for Data Science Machine Learning from | D03029C9B730E4036A994E7DA3B86E143FF93D69

2021 Python for Data Science Machine Learning from

Name	2021 Python for Data Science & Machine Learning from A-Z	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	7.9 GB
Total Files	429
Last Seen	2025-07-14 23:45
Hash	D03029C9B730E4036A994E7DA3B86E143FF93D69

/19. PCA/
7. PCA - Image Compression.mp4	262.1 MB
7. PCA - Image Compression.srt	40.3 KB
9. PCA - Biplot and the Screen Plot.mp4	142.2 MB
9. PCA - Biplot and the Screen Plot.srt	27.0 KB
8. PCA Data Preprocessing.srt	21.6 KB
4. PCA Algorithm Steps (Mathematics).srt	19.0 KB
2. What is PCA.srt	14.9 KB
10. PCA - Feature Scaling and Screen Plot.srt	14.7 KB
12. PCA - Visualization.srt	11.2 KB
11. PCA - Supervised vs Unsupervised.srt	7.3 KB
1. PCA Section Overview.srt	7.2 KB
5. Covariance Matrix vs SVD.srt	6.7 KB
3. PCA Drawbacks.srt	5.0 KB
6. PCA - Main Applications.srt	4.0 KB
8. PCA Data Preprocessing.mp4	126.3 MB
10. PCA - Feature Scaling and Screen Plot.mp4	71.5 MB
12. PCA - Visualization.mp4	71.3 MB
4. PCA Algorithm Steps (Mathematics).mp4	60.5 MB
2. What is PCA.mp4	49.6 MB
5. Covariance Matrix vs SVD.mp4	40.6 MB
11. PCA - Supervised vs Unsupervised.mp4	37.5 MB
1. PCA Section Overview.mp4	33.3 MB
3. PCA Drawbacks.mp4	20.4 MB
6. PCA - Main Applications.mp4	10.5 MB
/
TutsNode.com.txt	0.1 KB
[TGx]Downloaded from torrentgalaxy.to .txt	0.6 KB
/.../6. NumPy Data Analysis/
1.1 NumPy Basics.pdf	79.0 KB
1. Intro NumPy Array Data Types.srt	18.7 KB
3. NumPy Arrays Basics.srt	17.2 KB
4. NumPy Array Indexing.srt	14.4 KB
2. NumPy Arrays.srt	11.4 KB
5. NumPy Array Computations.srt	8.8 KB
6. Broadcasting.srt	6.5 KB
3. NumPy Arrays Basics.mp4	41.9 MB
4. NumPy Array Indexing.mp4	36.4 MB
1. Intro NumPy Array Data Types.mp4	36.4 MB
2. NumPy Arrays.mp4	33.9 MB
6. Broadcasting.mp4	18.7 MB
5. NumPy Array Computations.mp4	17.8 MB
/.pad/
0	1.9 KB
1	0.4 KB
2	0.0 KB
3	0.3 KB
4	0.0 KB
5	2.1 KB
6	0.0 KB
7	0.1 KB
8	373.6 KB
9	845.8 KB
10	61.9 KB
11	568.3 KB
12	34.5 KB
13	473.1 KB
14	651.7 KB
15	401.2 KB
16	861.2 KB
17	459.9 KB
18	79.5 KB
19	301.4 KB
20	29.4 KB
21	730.9 KB
22	5.3 KB
23	26.7 KB
24	250.1 KB
25	61.8 KB
26	760.4 KB
27	619.4 KB
28	916.1 KB
29	764.5 KB
30	206.2 KB
31	550.4 KB
32	22.0 KB
33	200.4 KB
34	1.0 MB
35	83.6 KB
36	965.0 KB
37	948.1 KB
38	782.2 KB
39	839.8 KB
40	869.8 KB
41	1.0 MB
42	378.8 KB
43	439.9 KB
44	40.6 KB
45	512.6 KB
46	431.0 KB
47	604.4 KB
48	283.5 KB
49	768.9 KB
50	128.1 KB
51	407.6 KB
52	488.3 KB
53	463.0 KB
54	523.1 KB
55	638.2 KB
56	150.6 KB
57	272.0 KB
58	778.6 KB
59	977.2 KB
60	65.3 KB
61	177.9 KB
62	11.8 KB
63	1.0 MB
64	1.0 MB
65	22.7 KB
66	350.3 KB
67	408.3 KB
68	270.9 KB
69	780.5 KB
70	841.5 KB
71	963.5 KB
72	221.9 KB
73	587.3 KB
74	721.3 KB
75	956.0 KB
76	270.2 KB
77	341.2 KB
78	405.7 KB
79	615.3 KB
80	321.4 KB
81	698.6 KB
82	241.9 KB
83	351.2 KB
84	208.6 KB
85	534.6 KB
86	538.6 KB
87	575.8 KB
88	797.4 KB
89	832.7 KB
90	470.6 KB
91	546.8 KB
92	594.4 KB
93	606.3 KB
94	81.0 KB
95	368.7 KB
96	594.9 KB
97	874.5 KB
98	561.9 KB
99	412.5 KB
100	413.2 KB
101	494.4 KB
102	4.2 KB
103	369.3 KB
104	451.6 KB
105	319.7 KB
106	450.2 KB
107	45.9 KB
108	541.2 KB
109	592.0 KB
110	796.9 KB
111	980.7 KB
112	327.6 KB
113	591.0 KB
114	655.1 KB
115	855.8 KB
116	618.1 KB
117	684.5 KB
118	146.2 KB
119	146.5 KB
120	883.4 KB
121	47.0 KB
122	67.6 KB
123	567.8 KB
124	710.4 KB
125	970.4 KB
126	51.7 KB
127	75.7 KB
128	383.4 KB
129	664.3 KB
130	931.8 KB
131	293.8 KB
132	453.7 KB
133	512.3 KB
134	113.8 KB
135	994.3 KB
136	104.2 KB
137	779.4 KB
138	956.6 KB
/.../16. Ensemble Learning and Random Forests/
6. Implementing Random Forests from scratch Part 1.mp4	212.4 MB
6. Implementing Random Forests from scratch Part 1.srt	30.8 KB
13. AdaBoost Part 2.srt	21.4 KB
2. What is Ensemble Learning.srt	17.8 KB
3. What is Bootstrap Sampling.srt	11.4 KB
5. Out-of-Bag Error (OOB Error).srt	10.2 KB
7. Implementing Random Forests from scratch Part 2.srt	8.5 KB
10. Random Forests Pros and Cons.srt	8.0 KB
4. What is Bagging.srt	7.9 KB
11. What is Boosting.srt	7.0 KB
9. Random Forests Hyper-Parameters.srt	6.1 KB
12. AdaBoost Part 1.srt	5.6 KB
1. Ensemble Learning Section Overview.srt	5.3 KB
8. Compare with sklearn implementation.srt	5.1 KB
2. What is Ensemble Learning.mp4	96.4 MB
13. AdaBoost Part 2.mp4	90.1 MB
3. What is Bootstrap Sampling.mp4	58.6 MB
7. Implementing Random Forests from scratch Part 2.mp4	53.0 MB
5. Out-of-Bag Error (OOB Error).mp4	44.1 MB
9. Random Forests Hyper-Parameters.mp4	41.6 MB
11. What is Boosting.mp4	37.2 MB
4. What is Bagging.mp4	30.9 MB
8. Compare with sklearn implementation.mp4	29.0 MB
12. AdaBoost Part 1.mp4	26.8 MB
10. Random Forests Pros and Cons.mp4	20.6 MB
1. Ensemble Learning Section Overview.mp4	16.9 MB
/.../3. Python For Data Science/
3.1 Jupyter Notebook.pdf	314.5 KB
2.2 Python Basics.pdf	130.8 KB
2.1 Importing Python Data.pdf	63.0 KB
7. Python Operators.srt	32.2 KB
15. Python Dictionaries.srt	28.4 KB
13. More about Lists.srt	19.9 KB
19. Object Oriented Programming in Python.srt	26.3 KB
18. Python Functions.srt	21.3 KB
10. Python Conditional Statements.srt	18.6 KB
17. Compound Data Types & When to use each one.srt	18.4 KB
9. Python Strings.srt	16.5 KB
5. Python Variables, Booleans and None.srt	15.6 KB
14. Python Tuples.srt	15.3 KB
16. Python Sets.srt	13.8 KB
6. Getting Started with Google Colab.srt	12.7 KB
11. Python For Loops and While Loops.srt	11.0 KB
8. Python Numbers & Booleans.srt	9.8 KB
1. What is Programming.srt	9.2 KB
12. Python Lists.srt	7.3 KB
2. Why Python for Data Science.srt	6.9 KB
3. What is Jupyter.srt	6.1 KB
4. What is Google Colab.srt	5.0 KB
15. Python Dictionaries.mp4	109.2 MB
7. Python Operators.mp4	91.0 MB
19. Object Oriented Programming in Python.mp4	73.7 MB
18. Python Functions.mp4	65.5 MB
13. More about Lists.mp4	63.4 MB
9. Python Strings.mp4	59.0 MB
10. Python Conditional Statements.mp4	57.3 MB
14. Python Tuples.mp4	57.2 MB
17. Compound Data Types & When to use each one.mp4	49.4 MB
5. Python Variables, Booleans and None.mp4	40.1 MB
6. Getting Started with Google Colab.mp4	36.8 MB
16. Python Sets.mp4	30.9 MB
8. Python Numbers & Booleans.mp4	26.9 MB
11. Python For Loops and While Loops.mp4	26.8 MB
12. Python Lists.mp4	22.5 MB
1. What is Programming.mp4	19.2 MB
2. Why Python for Data Science.mp4	17.1 MB
3. What is Jupyter.mp4	15.3 MB
4. What is Google Colab.mp4	8.7 MB
/18. K-means/
1. Unsupervised Machine Learning Intro.srt	30.1 KB
2. Unsupervised Machine Learning Continued.srt	29.9 KB
3. Representing Clusters.srt	29.0 KB
1.1 Unsupervised Learning.pdf	651.8 KB
3. Representing Clusters.mp4	114.9 MB
1. Unsupervised Machine Learning Intro.mp4	105.8 MB
2. Unsupervised Machine Learning Continued.mp4	87.2 MB
/.../15. Decision Trees/
7. ID3 - Putting Everything Together.mp4	191.3 MB
7. ID3 - Putting Everything Together.srt	31.8 KB
3. What is Entropy and Information Gain.srt	30.0 KB
3. What is Entropy and Information Gain.mp4	142.7 MB
8. Evaluating our ID3 implementation.srt	25.1 KB
13. Pruning.srt	24.9 KB
2. EDA on Adult Dataset.srt	24.3 KB
12. Decision Trees Hyper-parameters.srt	16.5 KB
10. Visualizing the tree.srt	15.4 KB
4. The Decision Tree ID3 algorithm from scratch Part 1.srt	15.3 KB
9. Compare with Sklearn implementation.srt	12.6 KB
5. The Decision Tree ID3 algorithm from scratch Part 2.srt	10.9 KB
15. Decision Trees Pros and Cons.srt	10.9 KB
16. [Project] Predict whether income exceeds $50Kyr - Overview.srt	3.7 KB
11. Plot the features importance.srt	7.9 KB
6. The Decision Tree ID3 algorithm from scratch Part 3.srt	5.9 KB
1. Decision Trees Section Overview.srt	5.7 KB
14. [Optional] Gain Ration.srt	3.8 KB
2. EDA on Adult Dataset.mp4	129.2 MB
8. Evaluating our ID3 implementation.mp4	127.9 MB
13. Pruning.mp4	118.5 MB
4. The Decision Tree ID3 algorithm from scratch Part 1.mp4	89.4 MB
12. Decision Trees Hyper-parameters.mp4	85.2 MB
10. Visualizing the tree.mp4	71.5 MB
9. Compare with Sklearn implementation.mp4	68.8 MB
5. The Decision Tree ID3 algorithm from scratch Part 2.mp4	67.1 MB
15. Decision Trees Pros and Cons.mp4	50.1 MB
6. The Decision Tree ID3 algorithm from scratch Part 3.mp4	35.0 MB
11. Plot the features importance.mp4	33.2 MB
14. [Optional] Gain Ration.mp4	20.1 MB
1. Decision Trees Section Overview.mp4	17.3 MB
16. [Project] Predict whether income exceeds $50Kyr - Overview.mp4	15.8 MB
/.../7. Pandas Data Analysis/
1.1 Pandas.pdf	112.8 KB
1.2 Pandas Basics.pdf	78.9 KB
2. Introduction to Pandas Continued.srt	27.5 KB
1. Introduction to Pandas.srt	22.8 KB
2. Introduction to Pandas Continued.mp4	74.5 MB
1. Introduction to Pandas.mp4	49.1 MB
/.../13. Linear and Logistic Regression/
3. Linear Regression + Correlation Methods.srt	39.5 KB
1. Linear Regression Intro.srt	12.5 KB
2. Gradient Descent.srt	8.6 KB
4. Linear Regression Implementation.srt	7.0 KB
5. Logistic Regression.srt	5.1 KB
3. Linear Regression + Correlation Methods.mp4	115.7 MB
1. Linear Regression Intro.mp4	32.3 MB
4. Linear Regression Implementation.mp4	18.7 MB
2. Gradient Descent.mp4	16.7 MB
5. Logistic Regression.mp4	9.3 MB
/9. Machine Learning/
1. Introduction To Machine Learning.srt	37.9 KB
1.1 Supervised Learning.pdf	856.8 KB
1. Introduction To Machine Learning.mp4	103.5 MB
/.../8. Python Data Visualization/
1. Data Visualization Overview.srt	37.7 KB
2. Different Data Visualization Libraries in Python.srt	9.0 KB
3. Python Data Visualization Implementation.srt	12.7 KB
1. Data Visualization Overview.mp4	76.6 MB
3. Python Data Visualization Implementation.mp4	28.8 MB
2. Different Data Visualization Libraries in Python.mp4	16.7 MB
/.../14. K Nearest Neighbors/
3. EDA on Iris Dataset.srt	32.4 KB
3. EDA on Iris Dataset.mp4	169.7 MB
5. Implement the KNN algorithm from scratch.srt	17.6 KB
7. Hyperparameter tuning using the cross-validation.srt	15.0 KB
11. Curse of dimensionality.srt	9.8 KB
10. Feature scaling in KNN.srt	8.3 KB
9. Manhattan vs Euclidean Distance.srt	7.9 KB
13. KNN pros and cons.srt	7.9 KB
8. The decision boundary visualization.srt	7.2 KB
6. Compare the result with the sklearn library.srt	5.2 KB
12. KNN use cases.srt	5.0 KB
2. parametric vs non-parametric models.srt	4.8 KB
1. KNN Overview.srt	4.4 KB
4. The KNN Intuition.srt	3.1 KB
7. Hyperparameter tuning using the cross-validation.mp4	94.7 MB
5. Implement the KNN algorithm from scratch.mp4	91.2 MB
10. Feature scaling in KNN.mp4	51.8 MB
11. Curse of dimensionality.mp4	48.2 MB
9. Manhattan vs Euclidean Distance.mp4	32.0 MB
13. KNN pros and cons.mp4	31.9 MB
12. KNN use cases.mp4	30.3 MB
6. Compare the result with the sklearn library.mp4	25.8 MB
8. The decision boundary visualization.mp4	17.8 MB
2. parametric vs non-parametric models.mp4	16.4 MB
1. KNN Overview.mp4	13.5 MB
4. The KNN Intuition.mp4	8.5 MB
/1. Introduction/
6. How To Get a Data Science Job.srt	31.4 KB
5. What is a Data Scientist.srt	27.5 KB
7. Data Science Projects Overview.srt	19.5 KB
6. How To Get a Data Science Job.mp4	137.6 MB
5. What is a Data Scientist.mp4	133.7 MB
4. Data Science Job Roles.srt	16.1 KB
2. Data Science + Machine Learning Marketplace.srt	10.7 KB
3. Data Science Job Opportunities.srt	7.0 KB
1. Who is This Course For.srt	4.0 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	30.9 MB
1. Who is This Course For.mp4	18.0 MB
/.../4. Statistics for Data Science/
2. Descriptive Statistics.srt	10.3 KB
6. Inferential Statistics.srt	22.6 KB
3. Measure of Variability.srt	18.6 KB
7. Measure of Asymmetry.srt	2.8 KB
4. Measure of Variability Continued.srt	13.6 KB
1. Intro To Statistics.srt	11.4 KB
5. Measures of Variable Relationship.srt	11.0 KB
8. Sampling Distribution.srt	10.5 KB
6. Inferential Statistics.mp4	47.2 MB
3. Measure of Variability.mp4	40.1 MB
4. Measure of Variability Continued.mp4	36.3 MB
8. Sampling Distribution.mp4	27.7 MB
5. Measures of Variable Relationship.mp4	24.7 MB
2. Descriptive Statistics.mp4	22.5 MB
1. Intro To Statistics.mp4	22.3 MB
7. Measure of Asymmetry.mp4	7.1 MB
/.../17. Support Vector Machines/
6. SVM - Kernel Types.srt	27.4 KB
7. SVM with Linear Dataset (Iris).srt	20.3 KB
3. Hard vs Soft Margins.srt	19.4 KB
8. SVM with Non-linear Dataset.srt	18.8 KB
5. Kernel Trick.srt	18.6 KB
2. SVM intuition.srt	16.4 KB
9. SVM with Regression.srt	8.2 KB
6. SVM - Kernel Types.mp4	132.5 MB
1. SVM Outline.srt	7.6 KB
10. SMV - Project Overview.srt	6.4 KB
4. C hyper-parameter.srt	5.8 KB
8. SVM with Non-linear Dataset.mp4	117.0 MB
7. SVM with Linear Dataset (Iris).mp4	106.5 MB
5. Kernel Trick.mp4	80.8 MB
3. Hard vs Soft Margins.mp4	68.8 MB
2. SVM intuition.mp4	51.2 MB
10. SMV - Project Overview.mp4	41.5 MB
1. SVM Outline.mp4	37.0 MB
9. SVM with Regression.mp4	26.2 MB
4. C hyper-parameter.mp4	22.1 MB
/.../2. Data Science & Machine Learning Concepts/
4. Machine Learning Concepts & Algorithms.srt	24.1 KB
3. What is Machine Learning.srt	23.5 KB
2. What is Data Science.srt	21.7 KB
6. Machine Learning vs Deep Learning.srt	18.3 KB
5. What is Deep Learning.srt	16.2 KB
1. Why We Use Python.srt	5.0 KB
2. What is Data Science.mp4	92.3 MB
3. What is Machine Learning.mp4	87.5 MB
4. Machine Learning Concepts & Algorithms.mp4	81.8 MB
5. What is Deep Learning.mp4	81.6 MB
6. Machine Learning vs Deep Learning.mp4	79.6 MB
1. Why We Use Python.mp4	14.2 MB
/.../10. Data Loading & Exploration/
1. Exploratory Data Analysis.srt	19.5 KB
1. Exploratory Data Analysis.mp4	53.0 MB
/.../5. Probability & Hypothesis Testing/
4. Hypothesis Testing Overview.srt	14.9 KB
3. Relative Frequency.srt	8.9 KB
1. What is Exactly is Probability.srt	6.9 KB
2. Expected Values.srt	4.2 KB
4. Hypothesis Testing Overview.mp4	63.5 MB
3. Relative Frequency.mp4	34.3 MB
1. What is Exactly is Probability.mp4	28.5 MB
2. Expected Values.mp4	15.4 MB
/.../11. Data Cleaning/
1. Feature Scaling.srt	11.9 KB
2. Data Cleaning.srt	11.8 KB
2. Data Cleaning.mp4	31.7 MB
1. Feature Scaling.mp4	20.3 MB
/.../20. Data Science Career/
1. Creating A Data Science Resume.srt	10.8 KB
5. Top Freelance Websites.srt	8.6 KB
3. How to Contact Recruiters.srt	7.5 KB
4. Getting Started with Freelancing.srt	7.2 KB
6. Personal Branding.srt	6.6 KB
7. Networking Do's and Don'ts.srt	6.4 KB
2. Data Science Cover Letter.srt	6.1 KB
8. Importance of a Website.srt	4.9 KB
1. Creating A Data Science Resume.mp4	38.9 MB
6. Personal Branding.mp4	32.0 MB
4. Getting Started with Freelancing.mp4	31.7 MB
5. Top Freelance Websites.mp4	31.0 MB
3. How to Contact Recruiters.mp4	25.8 MB
7. Networking Do's and Don'ts.mp4	24.8 MB
2. Data Science Cover Letter.mp4	24.1 MB
8. Importance of a Website.mp4	16.1 MB
/.../12. Feature Selecting and Engineering/
1. Feature Engineering.srt	9.7 KB
1. Feature Engineering.mp4	19.3 MB
Total files 429