Udemy - Data Science Mastery - Journey into Machine Learning

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Free Download Udemy - Data Science Mastery - Journey into Machine Learning
Last updated: 4/2025
Created by: Tech Career World
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English + subtitle | Duration: 530 Lectures ( 49h 5m ) | Size: 15.6 GB

Learn Machine Learning, Data Science and Deep Learning with Python
What you'll learn
Gain proficiency in using Python libraries commonly used in data science and machine learning, such as NumPy, Pandas, and Matplotlib.
Learn how to clean and preprocess datasets, including handling missing data, outliers, and feature scaling.
Acquire knowledge of exploratory data analysis techniques to extract insights and patterns from data.
Master the fundamentals of statistical analysis and apply statistical methods to interpret and draw conclusions from data.
Understand the principles of machine learning and its various algorithms, such as regression, classification, and clustering.
Learn how to select appropriate machine learning models and techniques for different types of problems and datasets.
Develop skills in feature engineering and selection to enhance the performance of machine learning models.
Requirements
Just passion for learning!
Description
The Python for Data Science and Machine Learning course is designed to equip learners with a comprehensive understanding of Python programming, data science techniques, and machine learning algorithms. Whether you are a beginner looking to enter the field or a seasoned professional seeking to expand your skillset, this course provides the knowledge and practical experience necessary to excel in the rapidly growing field of data science.Course Objectives:1. Master Python Programming: Develop a strong foundation in Python programming, including syntax, data structures, control flow, and functions. Gain proficiency in using Python libraries such as NumPy, Pandas, and Matplotlib to manipulate and visualize data effectively.2. Data Cleaning and Preprocessing: Learn how to handle missing data, outliers, and inconsistent data formats. Acquire skills in data cleaning and preprocessing techniques to ensure the quality and reliability of datasets.3. Exploratory Data Analysis: Understand the principles and techniques of exploratory data analysis. Learn how to extract insights, discover patterns, and visualize data using statistical methods and Python libraries.4. Statistical Analysis: Gain a solid understanding of statistical concepts and techniques. Apply statistical methods to analyze data, test hypotheses, and draw meaningful conclusions.5. Machine Learning Fundamentals: Learn the foundations of machine learning, including supervised and unsupervised learning, regression, classification, and clustering. Understand the strengths and limitations of different machine learning algorithms.6. Machine Learning Implementation: Gain hands-on experience in implementing machine learning models using Python libraries such as scikit-learn. Learn how to train, evaluate, and optimize machine learning models.7. Feature Engineering and Selection: Develop skills in feature engineering to create meaningful and informative features from raw data. Learn techniques for feature selection to improve model performance and interpretability.8. Model Evaluation and Optimization: Learn how to assess the performance of machine learning models using techniques like cross-validation and evaluation metrics. Understand the importance of hyperparameter tuning and regularization for model optimization.9. Deep Learning Concepts: Explore the basics of deep learning, including neural networks, activation functions, and gradient descent optimization. Gain an understanding of deep learning architectures and their applications.10. Practical Deep Learning: Acquire practical experience in building and training neural networks using popular deep learning frameworks such as TensorFlow or PyTorch. Learn how to apply deep learning techniques to solve real-world problems.
Who this course is for
Aspiring data scientists and machine learning enthusiasts who have a basic understanding of Python programming.
Learners who want to acquire comprehensive knowledge and practical skills in Python, data science, and machine learning.
The course content is tailored to provide valuable insights and hands-on experience to individuals aiming to excel in data-driven problem-solving and analysis.
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15.64 GB | 15min 50s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

1 -Introduction to Numpy.mp4 (24.22 MB)
10 -Fancy Indexing in Numpy.mp4 (17.12 MB)
11 -Transposing and Swapping.mp4 (20.36 MB)
12 -Universal Functions.mp4 (26.68 MB)
13 -Array Oriented Programming.mp4 (24.45 MB)
14 -Expressing Conditional Logic.mp4 (28.57 MB)
15 -Methods involving Math and Statistics.mp4 (22.02 MB)
16 -Boolean Array Methods.mp4 (9.39 MB)
17 -The Sorting.mp4 (16.65 MB)
18 -Unique Set Logic.mp4 (15.02 MB)
19 -Linear Algebra.mp4 (24.3 MB)
2 -Numpy ndarray.mp4 (16.58 MB)
20 -Pseudorandom Number Generator.mp4 (21.68 MB)
21 -Random Walks (An example).mp4 (27.45 MB)
22 -Simulation of plenty of Random Walks.mp4 (23.26 MB)
3 -ndarray.mp4 (23.66 MB)
4 -Data Types.mp4 (47.64 MB)
5 -Arithmetic.mp4 (16.9 MB)
6 -Indexing and Slicing.mp4 (18.04 MB)
7 -Indexing and Slicing - 2.mp4 (22.87 MB)
8 -Indexing and Slicing - 3.mp4 (16 MB)
9 -Boolean Indexing.mp4 (41.32 MB)
1 -Object Internals.mp4 (16.69 MB)
10 -Setting Array Values.mp4 (10.83 MB)
11 -ufunc Instance Methods.mp4 (47.09 MB)
12 -Writing New ufuncs.mp4 (21.34 MB)
13 -Structured, Record Arrays and Nested dtypes.mp4 (35.35 MB)
14 -More about Sorting.mp4 (22.97 MB)
15 -argsort and lexsort.mp4 (34.18 MB)
16 -Alternative Sort Algorithms and Partially Sorting Arrays.mp4 (29.1 MB)
17 -numpy searchsorted.mp4 (21.55 MB)
18 -Numba.mp4 (36.24 MB)
19 -Identifiers.mp4 (12.03 MB)
2 -dtype Hierarchy.mp4 (18.85 MB)
20 -Reserve Words.mp4 (8.16 MB)
21 -Strings.mp4 (18.37 MB)
3 -Reshaping Arrays.mp4 (18.98 MB)
4 -C vs Fortran Order.mp4 (10.42 MB)
5 -Splitting and Concatenating Arrays and r and c.mp4 (39.71 MB)
6 -tile and repeat.mp4 (23.87 MB)
7 -take and put.mp4 (13.72 MB)
8 -Broadcasting.mp4 (24.23 MB)
9 -Broadcasting Over Other Axes.mp4 (36.6 MB)
1 -Welcome to the Series.mp4 (21.97 MB)
10 -Value Membership, Deleting and Filtering.mp4 (15.57 MB)
11 -Nested Dict and Transposition.mp4 (23.48 MB)
12 -Methods and Duplicate Labels.mp4 (28.87 MB)
13 -Reindexing.mp4 (34.25 MB)
14 -Dropping.mp4 (21.89 MB)
15 -Arithmetic and Data Alignment.mp4 (33.26 MB)
16 -Arithmetic Methods.mp4 (10.07 MB)
17 -DataFrame and Series and Operations.mp4 (19.43 MB)
18 -Functions by Element and Row or Column and Statistics.mp4 (42.27 MB)
19 -Ranking and Sorting.mp4 (40.52 MB)
2 -Internal Elements and Assigning Values.mp4 (11.23 MB)
20 -Covariance and Correlation.mp4 (57.33 MB)
21 -Assigning a NaN Value.mp4 (12.98 MB)
22 -NaN Value Filtration.mp4 (27.3 MB)
23 -Filling.mp4 (9.09 MB)
24 -Hierarchical Indexing.mp4 (48.55 MB)
25 -Sorting Levels and Reordering.mp4 (17.75 MB)
26 -Summary Statistic.mp4 (6.91 MB)
3 -Defining Series and Filtering Values.mp4 (12.85 MB)
4 -Mathematical Functions and Evaluating Values.mp4 (22.27 MB)
5 -NaN Values.mp4 (13.41 MB)
6 -Dictionaries and Operations between Series.mp4 (23.22 MB)
7 -DataFrame.mp4 (47.77 MB)
8 -Selecting Elements.mp4 (24.51 MB)
9 -Assigning Values.mp4 (21.11 MB)
1 -Introduction to Data Manipulation.mp4 (12.52 MB)
10 -Removing.mp4 (13.07 MB)
11 -Duplicates Removal.mp4 (21.11 MB)
12 -Replacing Values via Mapping.mp4 (39.68 MB)
13 -Adding Values.mp4 (27.19 MB)
14 -Indexes of the Axes.mp4 (24.22 MB)
15 -Binning and Discretization.mp4 (46.69 MB)
16 -Filtering Outliers.mp4 (17.07 MB)
17 -Permutation.mp4 (19.87 MB)
18 -Built-in Methods of Strings.mp4 (50.42 MB)
19 -Regex (Regular Expressions).mp4 (58.93 MB)
2 -Merging.mp4 (34.67 MB)
20 -GroupBy.mp4 (17.43 MB)
21 -Example.mp4 (32.95 MB)
22 -Hierarchical Grouping.mp4 (16.22 MB)
23 -Group Iteration and Transformations.mp4 (33.12 MB)
24 -Functions.mp4 (14.6 MB)
25 -Advanced Data Aggregation.mp4 (24.39 MB)
26 -Advanced Data Aggregation - 2.mp4 (45.26 MB)
3 -Merging - 2.mp4 (33.96 MB)
4 -Merging - 3.mp4 (35.55 MB)
5 -Merging on Index.mp4 (15.39 MB)
6 -Concatenating.mp4 (56.86 MB)
7 -Combining.mp4 (18.35 MB)
8 -Pivoting with Hierarchical Indexing.mp4 (21.09 MB)
9 -Long or Stacked Format.mp4 (34.61 MB)
1 -Introduction in Data Visualization.mp4 (22.82 MB)
10 -Adding a Legend - 2.mp4 (27.03 MB)
11 -Handling Date Values.mp4 (57.38 MB)
12 -Line Chart.mp4 (27.47 MB)
13 -Line Chart - 2.mp4 (17.83 MB)
14 -Line Chart - 3.mp4 (38.74 MB)
15 -Line Chart - 4.mp4 (78.45 MB)
16 -Line Chart with pandas.mp4 (14.22 MB)
17 -Histogram.mp4 (13.85 MB)
18 -The Bar Chart.mp4 (44.84 MB)
19 -Horizontal Bar Chart.mp4 (56.04 MB)
2 -pyplot.mp4 (11.07 MB)
20 -Multiseries with pandas.mp4 (11.65 MB)
21 -Multiseries Stacked.mp4 (31.12 MB)
22 -Multiseries Stacked - 2.mp4 (47.3 MB)
23 -Stacked Bar Charts with pandas and Facecolor.mp4 (47.1 MB)
24 -Pie Chart.mp4 (18.61 MB)
25 -Pie Chart - 2.mp4 (33.06 MB)
26 -Pie Chart with pandas.mp4 (12.88 MB)
27 -Contour Plot.mp4 (45.69 MB)
28 -Polar Charts.mp4 (37.83 MB)
29 -3D Surfaces.mp4 (46.45 MB)
3 -Properties of the Plot.mp4 (25.17 MB)
30 -Scatter Plot in 3D.mp4 (33.99 MB)
31 -Bar Chart 3D.mp4 (34.28 MB)
32 -Multi-Panel Plots.mp4 (18.11 MB)
33 -Grids of Subplots.mp4 (38.69 MB)
4 -Numpy and Matplotlib.mp4 (30.78 MB)
5 -Kwargs.mp4 (9.3 MB)
6 -Multiple Figures and Axes.mp4 (30.9 MB)
7 -Adding the Text.mp4 (49 MB)
8 -Adding a Grid.mp4 (26.18 MB)
9 -Adding a Legend.mp4 (29.11 MB)
1 -Machine Learning.mp4 (8.04 MB)
10 -Linear Regression- Least Square Regression.mp4 (27.76 MB)
11 -Linear Correlation Between Feature.mp4 (54.46 MB)
12 -Correlations between Psychological Factors.mp4 (34.27 MB)
13 -Support Vector Machine.mp4 (39.27 MB)
14 -Decision Area Split Graph.mp4 (44.14 MB)
15 -Decreasing C Points.mp4 (56.81 MB)
16 -Decisional Area using SVC With RGB Kernel.mp4 (61.3 MB)
17 -Different SVM Classifiers using Iris Dataset.mp4 (63.28 MB)
18 -Support Vector Regression (SVR).mp4 (39.27 MB)
2 -Supervised and Unsupervised Learning.mp4 (16.02 MB)
3 -Iris Flower Dataset.mp4 (18.54 MB)
4 -Iris Flower Dataset - 2.mp4 (39.9 MB)
5 -Iris Flower Dataset - 3.mp4 (21.46 MB)
6 -Principal Component Analysis.mp4 (56.6 MB)
7 -K-Nearest Neighbors Classifier.mp4 (31.06 MB)
8 -K-Nearest Neighbors Classifier - 2.mp4 (106.17 MB)
9 -Diabetes Dataset.mp4 (27.31 MB)
1 -Introduction.mp4 (31.57 MB)
10 -Slicing.mp4 (26.21 MB)
11 -Iteration.mp4 (29.26 MB)
12 -Boolean Arrays and Conditions.mp4 (19.1 MB)
13 -Shape Manipulation.mp4 (24.23 MB)
14 -Joining Arrays.mp4 (22.46 MB)
15 -hsplit() and vsplit().mp4 (34.29 MB)
16 -Copies.mp4 (18.18 MB)
17 -Vectorization.mp4 (24.3 MB)
18 -Broadcasting.mp4 (41.66 MB)
19 -Structured Arrays.mp4 (53.98 MB)
2 -Array.mp4 (13.51 MB)
3 -Data Types.mp4 (23.5 MB)
4 -dtype Option and Array Creation.mp4 (39.68 MB)
5 -Arithmetic Operators.mp4 (23.84 MB)
6 -The Matrix.mp4 (11.39 MB)
7 -Increment and Decrement.mp4 (12.48 MB)
8 -ufunc and Aggregate Functions.mp4 (19.18 MB)
9 -Indexing.mp4 (22.09 MB)
1 -Introduction.mp4 (16.72 MB)
10 -str and repr.mp4 (17.52 MB)
11 -Long Strings.mp4 (21.47 MB)
12 -Raw Strings.mp4 (46.73 MB)
13 -Bytearray and Unicode.mp4 (73.33 MB)
2 -Numbers and Variables.mp4 (46.42 MB)
3 -Statements.mp4 (17.33 MB)
4 -Getting Input.mp4 (20.55 MB)
5 -Functions.mp4 (18.24 MB)
6 -Modules and cmath.mp4 (37.49 MB)
7 -Comments.mp4 (16.97 MB)
8 -Strings.mp4 (32.95 MB)
9 -Concatenation.mp4 (13.85 MB)
1 -Tuples and Lists.mp4 (19.93 MB)
10 -List Function.mp4 (5.16 MB)
11 -Item Assignments, Deleting and Assigning.mp4 (38.86 MB)
12 -append, copy and copy.mp4 (22.59 MB)
13 -count and extend.mp4 (24.88 MB)
14 -insert and pop.mp4 (22.79 MB)
15 -remove, reverse and sort.mp4 (49.59 MB)
16 -Tuples.mp4 (21.93 MB)
2 -Indexing.mp4 (50.76 MB)
3 -Slicing.mp4 (16.22 MB)
4 -Shortcut.mp4 (27.46 MB)
5 -Thats Long.mp4 (26.12 MB)
6 -Sequences and Multiplication.mp4 (11.02 MB)
7 -Initialization and Empty Lists.mp4 (44.71 MB)
8 -Membership.mp4 (41.1 MB)
9 -Min, Max.mp4 (12.78 MB)
1 -Introduction.mp4 (77.81 MB)
2 -String Formatting.mp4 (46.61 MB)
3 -Some Basic Conversions.mp4 (40.13 MB)
4 -Precision, Width and Zero-Padding.mp4 (94.07 MB)
5 -String Methods.mp4 (34.01 MB)
6 -String Methods - 2.mp4 (18.01 MB)
7 -join and lower.mp4 (33.49 MB)
8 -replace, split, strip, translate.mp4 (35.27 MB)
1 -Introduction.mp4 (39.64 MB)
10 -pop and popitem.mp4 (19.61 MB)
11 -setdefault.mp4 (14.52 MB)
12 -update and values.mp4 (19.65 MB)
2 -dict Function.mp4 (14.23 MB)
3 -Operations.mp4 (63.79 MB)
4 -String Formatting.mp4 (25.45 MB)
5 -clear.mp4 (21.59 MB)
6 -copy.mp4 (19.85 MB)
7 -fromkeys.mp4 (13.67 MB)
8 -get.mp4 (42.62 MB)
9 -items.mp4 (18.48 MB)
1 -Introduction to Pandas.mp4 (7.71 MB)
10 -Reindexing.mp4 (14.07 MB)
11 -Reindexing - 2.mp4 (20.57 MB)
12 -Axis and the Dropping of Values.mp4 (24.75 MB)
13 -Indexing.mp4 (14.36 MB)
14 -Indexing - 2.mp4 (13.74 MB)
15 -Using loc and iloc for Selection.mp4 (31.13 MB)
16 -Integer Indexes.mp4 (15.58 MB)
17 -Data Alignment & Arithmetic.mp4 (17.46 MB)
18 -Data Alignment & Arithmetic - 2.mp4 (18.59 MB)
19 -Fill Values with Arithmetic Methods.mp4 (25.71 MB)
2 -Series.mp4 (15.55 MB)
20 -DataFrame and Series and the Operation.mp4 (26.93 MB)
21 -Application and Mapping.mp4 (14.4 MB)
22 -Application and Mapping - 2.mp4 (11.7 MB)
23 -Ranking and Sorting.mp4 (17.22 MB)
24 -Ranking and Sorting - 2.mp4 (29.93 MB)
25 -Axis Indexes.mp4 (12.43 MB)
26 -Computing Descriptive Statistics.mp4 (17.51 MB)
27 -Computing Descriptive Statistics - 2.mp4 (18.44 MB)
28 -Value Counts, Membership, Unique Values.mp4 (33.68 MB)
3 -Series - 2.mp4 (29.32 MB)
4 -Series - 3.mp4 (18.02 MB)
5 -DataFrame.mp4 (16.27 MB)
6 -DataFrame - 2.mp4 (24.69 MB)
7 -DataFrame - 3.mp4 (26.11 MB)
8 -DataFrame - 4.mp4 (22.44 MB)
9 -Index Objects.mp4 (27.44 MB)
1 -Introduction.mp4 (51.66 MB)
10 -String and Sequence.mp4 (19.08 MB)
11 -Boolean Operators and Assertions.mp4 (50.8 MB)
12 -while and for Loops.mp4 (67.78 MB)
13 -Parallel and Numbered Iteration.mp4 (55.65 MB)
2 -Assignment and Sequence.mp4 (38.11 MB)
3 -Chained and Augmented Assignment.mp4 (19.27 MB)
4 -Blocks.mp4 (17.12 MB)
5 -Conditional Statements.mp4 (23.72 MB)
6 -if Statement and else Clauses.mp4 (28.69 MB)
7 -elif Clauses and Nesting Blocks.mp4 (28.56 MB)
8 -Comparison Operators.mp4 (20.32 MB)
9 -Equality Operator, is and in Operator.mp4 (41.02 MB)
1 -Introduction.mp4 (33.37 MB)
2 -Introduction - 2.mp4 (58.29 MB)
3 -Hello from VP.mp4 (88.59 MB)
4 -Hello from VP - 2.mp4 (102.9 MB)
5 -Graphical Experience.mp4 (59.39 MB)
6 -Graphical Experience - 2.mp4 (45.63 MB)
1 -Introduction.mp4 (40.46 MB)
2 -Bar Charts.mp4 (27.17 MB)
3 -Bar Charts - 2.mp4 (47.91 MB)
4 -Bar Charts - 3.mp4 (54.84 MB)
5 -Line Charts.mp4 (38.15 MB)
6 -Scatterplots.mp4 (55.54 MB)
1 -Vectors.mp4 (22.53 MB)
2 -Vectors - 2.mp4 (42.76 MB)
3 -Vectors - 3.mp4 (50.01 MB)
4 -Matrices.mp4 (45.14 MB)
5 -Matrices - 2.mp4 (37.75 MB)
1 -Introduction.mp4 (44.17 MB)
2 -Statistics.mp4 (23.18 MB)
3 -Central Tendencies.mp4 (27.83 MB)
4 -Central Tendencies - 2.mp4 (29.58 MB)
5 -Dispersion.mp4 (65.73 MB)
6 -Correlation.mp4 (61.69 MB)
7 -Correlation - 2.mp4 (26.31 MB)
1 -Probability.mp4 (6.68 MB)
10 -Central Limit Theorem - 2.mp4 (67.1 MB)
2 -Dependence and Independence.mp4 (9.94 MB)
3 -Conditional Probability.mp4 (33.43 MB)
4 -Boy and Girl Probability.mp4 (26.92 MB)
5 -Bayes Theorem.mp4 (36.1 MB)
6 -Random Variables.mp4 (16.49 MB)
7 -Continuous Distributions.mp4 (24.4 MB)
8 -Normal Distribution.mp4 (43.43 MB)
9 -Central Limit Theorem.mp4 (54.11 MB)
1 -Hypothesis Testing and Coin Examples.mp4 (13.06 MB)
2 -Coin Example.mp4 (40.77 MB)
3 -Coin Example - 2.mp4 (38.82 MB)
4 -Coin Example - 3.mp4 (41.66 MB)
5 -Coin Example - 4.mp4 (63.47 MB)
6 -Confidence Interval.mp4 (32.7 MB)
7 -P-Hacking.mp4 (31.13 MB)
8 -AB Testing.mp4 (43.94 MB)
9 -Bayesian Inference.mp4 (52.14 MB)
1 -Gradient Descent.mp4 (19.96 MB)
2 -Estimating.mp4 (9.07 MB)
3 -Estimating - 2.mp4 (44.07 MB)
4 -Right Step Size.mp4 (17.01 MB)
5 -Additional Details.mp4 (54.78 MB)
6 -Stochastic Gradient Descent.mp4 (54.21 MB)
1 -Data Exploration and Working with Data.mp4 (44.51 MB)
10 -Rescaling.mp4 (43.68 MB)
11 -Rescaling - 2.mp4 (32.48 MB)
12 -Dimensionality Reduction.mp4 (44.56 MB)
13 -Dimensionality Reduction - 2.mp4 (55.65 MB)
14 -Dimensionality Reduction - 3.mp4 (39.63 MB)
2 -Two Dimensions.mp4 (35.46 MB)
3 -Plenty of Dimensions.mp4 (55.72 MB)
4 -Cleaning.mp4 (31.51 MB)
5 -Cleaning - 2.mp4 (57.93 MB)
6 -Manipulation.mp4 (35.21 MB)
7 -Manipulation - 2.mp4 (32.26 MB)
8 -Manipulation - 3.mp4 (23.63 MB)
9 -Manipulation - 4.mp4 (33.96 MB)
1 -Introduction to Machine Learning.mp4 (11.69 MB)
2 -Over-fitting and Under-fitting.mp4 (21.54 MB)
3 -Over-fitting and Under-fitting - 2.mp4 (17.81 MB)
4 -Over-fitting and Under-fitting - 3.mp4 (23.84 MB)
5 -Correctness.mp4 (31.76 MB)
6 -Correctness - 2.mp4 (32.58 MB)
7 -Bias-Variance Trade-Off.mp4 (15.14 MB)
1 -Lets Handle Missing Data.mp4 (23.29 MB)
10 -Discretization and Binning.mp4 (11.42 MB)
11 -Discretization and Binning - 2.mp4 (20.63 MB)
12 -Discretization and Binning - 3.mp4 (15.64 MB)
13 -Filtering and Detecting the Outliers.mp4 (17.46 MB)
14 -Random Sampling and Permutations.mp4 (15.23 MB)
15 -Indicator Computing.mp4 (15.08 MB)
16 -Indicator Computing - 2.mp4 (24.27 MB)
17 -Indicator Computing - 3.mp4 (23.53 MB)
18 -Indicator Computing - 4.mp4 (15.09 MB)
19 -String Object Methods.mp4 (18.28 MB)
2 -Filtration of the Missing Data.mp4 (26.44 MB)
20 -String Object Methods - 2.mp4 (16.34 MB)
21 -Regular Expressions.mp4 (16.48 MB)
22 -Regular Expressions - 2.mp4 (18.25 MB)
23 -Regular Expressions - 3.mp4 (32.49 MB)
24 -Vectorized String Functions.mp4 (28.09 MB)
25 -Vectorized String Functions - 2.mp4 (52.57 MB)
26 -Hierarchical Indexing.mp4 (12.91 MB)
27 -Hierarchical Indexing - 2.mp4 (15.57 MB)
28 -Hierarchical Indexing - 3.mp4 (25.19 MB)
29 -Reordering and the Sorting Levels.mp4 (9.91 MB)
3 -Filling of the Missing Data.mp4 (26.28 MB)
30 -Summarizing Statistics and Indexing with DataFrames Columns.mp4 (34.39 MB)
31 -DataFrame Join with Database Style.mp4 (23.02 MB)
32 -DataFrame Join with Database Style - 2.mp4 (20.58 MB)
33 -DataFrame Join with Database Style - 3.mp4 (43.31 MB)
34 -Merging on Index.mp4 (17.14 MB)
35 -Merging on Index - 2.mp4 (25 MB)
36 -Merging on Index - 3.mp4 (41.33 MB)
37 -Merging on Index - 4.mp4 (23.13 MB)
38 -Concatenating Along an Axis.mp4 (22.99 MB)
39 -Concatenating Along an Axis - 2.mp4 (31.34 MB)
4 -Duplicates Removal.mp4 (14.78 MB)
40 -Concatenating Along an Axis - 3.mp4 (39.62 MB)
41 -Data Combining with the Overlap.mp4 (32.1 MB)
42 -Hierarchical Indexing and Reshaping.mp4 (15.65 MB)
43 -Hierarchical Indexing and Reshaping - 2.mp4 (29.67 MB)
44 -pd melt.mp4 (24.36 MB)
5 -Function or Mapping and Transformation.mp4 (22.85 MB)
6 -Function or Mapping.mp4 (14.98 MB)
7 -Function or Mapping - 2.mp4 (17.19 MB)
8 -Values Replacing.mp4 (17.96 MB)
9 -Axis Indexes Renaming.mp4 (24.11 MB)
1 -K-Nearest Neighbors.mp4 (18.53 MB)
2 -Model.mp4 (37.71 MB)
3 -Model - 2.mp4 (13.15 MB)
4 -Example - Favorite Language.mp4 (55.21 MB)
5 -Example - Favorite Language - 2.mp4 (59.48 MB)
6 -Curse of Dimensionality.mp4 (56.49 MB)
7 -Curse of Dimensionality - 2.mp4 (22.68 MB)
1 -Naive Bayes.mp4 (24.82 MB)
2 -Sophisticated Spam Filter.mp4 (46.41 MB)
3 -Implementation.mp4 (23.54 MB)
4 -Implementation - 2.mp4 (67.16 MB)
1 -Simple Linear Regression.mp4 (29.36 MB)
2 -Model.mp4 (55.12 MB)
3 -Gradient Descent.mp4 (25.79 MB)
4 -Maximum Likelihood Estimation.mp4 (19.25 MB)
1 -Multiple Regression.mp4 (31.06 MB)
10 -Regularization - 3.mp4 (51.01 MB)
2 -Assumptions of Least Square Model.mp4 (27.72 MB)
3 -Fitting the Model.mp4 (26.37 MB)
4 -Goodness of Fit.mp4 (20.66 MB)
5 -Bootstrap.mp4 (37.12 MB)
6 -Standard Errors.mp4 (36.56 MB)
7 -Standard Errors - 2.mp4 (43.21 MB)
8 -Regularization.mp4 (17.04 MB)
9 -Regularization - 2.mp4 (39.93 MB)
1 -Logistic Regression.mp4 (36.11 MB)
2 -Logistic Regression - 2.mp4 (56.63 MB)
3 -Applying.mp4 (26.18 MB)
4 -Goodness of Fit.mp4 (40.1 MB)
1 -Decision Trees.mp4 (19.06 MB)
2 -Entropy.mp4 (41.58 MB)
3 -Entropy of a Partition.mp4 (27.84 MB)
4 -Creating a Decision Tree.mp4 (14.13 MB)
5 -Creating a Decision Tree - 2.mp4 (71.92 MB)
6 -Summing Up.mp4 (18.67 MB)
7 -Summing Up - 2.mp4 (82.82 MB)
8 -Random Forests.mp4 (34.16 MB)
1 -Perceptrons.mp4 (45.94 MB)
2 -Feed-Forward Neural Networks.mp4 (55.76 MB)
3 -Backpropagation.mp4 (67.82 MB)
4 -Defeating a CAPTCHA.mp4 (27.03 MB)
5 -Defeating a CAPTCHA - 2.mp4 (32.54 MB)
6 -Defeating a CAPTCHA - 3.mp4 (98.72 MB)
1 -Clusters.mp4 (13.99 MB)
2 -Model.mp4 (44.95 MB)
3 -Meetup.mp4 (28.09 MB)
4 -Choosing k.mp4 (29.42 MB)
1 -Data Visualization Project in Python.mp4 (8.74 MB)
2 -We will Cover.mp4 (17.53 MB)
3 -Importing Libraries.mp4 (5.63 MB)
4 -Generate Sample Sales Data.mp4 (24.28 MB)
5 -Line Chart - Sales Trend Over Time.mp4 (24.59 MB)
6 -Histogram - Distribution of Sales.mp4 (20.35 MB)
7 -Box Plot.mp4 (14.44 MB)
8 -Scatter Plot.mp4 (27.67 MB)
1 -Introduction.mp4 (11.12 MB)
10 -Bar Plots.mp4 (25.64 MB)
11 -Bar Plots - 2.mp4 (17.35 MB)
12 -Bar Plots - 3.mp4 (18.6 MB)
13 -Histograms.mp4 (21.65 MB)
14 -Scatter Plots.mp4 (46.19 MB)
15 -Categorical Data and Facet Grids.mp4 (26.84 MB)
2 -Figures and Subplots.mp4 (25.07 MB)
3 -Figures and Subplots - 2.mp4 (21.49 MB)
4 -Figures and Subplots - 3.mp4 (15.46 MB)
5 -Markers, Line Styles and Colors.mp4 (35.65 MB)
6 -Labels, Legends and Ticks, Title, Ticklabels, Titles.mp4 (35.49 MB)
7 -Labels, Legends and Ticks, Adding a Legend.mp4 (29.68 MB)
8 -Drawing on a Subplot.mp4 (23.53 MB)
9 -Line Plots.mp4 (32.18 MB)
1 -Introduction.mp4 (14.45 MB)
10 -Multiple Function Application and Column Wise.mp4 (21.69 MB)
11 -Multiple Function Application and Column Wise - 2.mp4 (35.65 MB)
12 -Returning Aggregated Data.mp4 (10.74 MB)
13 -Split-Apply-Combine.mp4 (30.92 MB)
14 -Group Keys and Quantile and Bucket Analysis.mp4 (35.96 MB)
15 -Example of Filling Missing Values with respect to the Group-Specific Values.mp4 (36.89 MB)
16 -Example of Random Sampling and Permutation.mp4 (29.35 MB)
17 -Example of Group Weighted Average and Correlation.mp4 (17.64 MB)
18 -Example of Group Weighted Average and Correlation - 2.mp4 (26.37 MB)
19 -Example of the Group-Wise Linear Regression.mp4 (18.44 MB)
2 -Mechanics of the GroupBy.mp4 (25.99 MB)
20 -Cross-Tabulation and Pivot Tables.mp4 (24.6 MB)
21 -Cross-Tabulation and Pivot Tables - 2.mp4 (24.87 MB)
22 -CrossTab.mp4 (13.46 MB)
3 -Mechanics of the GroupBy - 2.mp4 (32.86 MB)
4 -Iterating over the Groups.mp4 (23.36 MB)
5 -Selecting a Column.mp4 (16.42 MB)
6 -Grouping with Dicts.mp4 (26.37 MB)
7 -Grouping with Functions.mp4 (12.16 MB)
8 -Grouping with Functions - 2.mp4 (18.26 MB)
9 -Data Aggregation.mp4 (25.07 MB)
1 -Time Data Types and Tools and Data.mp4 (27.69 MB)
10 -Shifting Data.mp4 (18.83 MB)
11 -Shifting Dates with the Offsets.mp4 (21.84 MB)
12 -Time Zone Handling.mp4 (10.68 MB)
13 -Localization and Conversion of the Time.mp4 (37.49 MB)
14 -Aware Timestamp Objects.mp4 (27.69 MB)
15 -Different Time Zones and Operations Between Them.mp4 (13.61 MB)
16 -Period Arithmetic.mp4 (29.59 MB)
17 -Conversion of Period Frequency.mp4 (28.96 MB)
18 -Period Frequencies of Quarters.mp4 (24.66 MB)
19 -Conversion of Timestamps to Period & Back.mp4 (20.92 MB)
2 -Datetime and String Conversion Between Them.mp4 (19.66 MB)
20 -PeriodIndex from Arrays.mp4 (23.95 MB)
21 -Frequency Conversion and Resampling.mp4 (26.51 MB)
22 -Downsampling.mp4 (29.38 MB)
23 -Interpolation and Upsampling.mp4 (24.96 MB)
24 -Resampling with the Periods.mp4 (25 MB)
25 -Sliding Window.mp4 (45.84 MB)
26 -Exponentially Weighted Functions.mp4 (20.82 MB)
27 -Functions of the Binary Moving Window.mp4 (29.28 MB)
3 -Datetime and String Conversion Between Them - 2.mp4 (48.11 MB)
4 -Basics of Time Series.mp4 (17.15 MB)
5 -Subsetting, Indexing, Selection.mp4 (43.59 MB)
6 -Duplicate Indices and Time Series.mp4 (19.13 MB)
7 -Generation of the Date Ranges.mp4 (41.65 MB)
8 -Date Offsets and Frequencies.mp4 (21.39 MB)
9 -Week of Month Dates.mp4 (6 MB)
1 -Categorical Data.mp4 (31.22 MB)
10 -Pipe.mp4 (29.4 MB)
2 -Categorical Type.mp4 (55.93 MB)
3 -Computations with Categoricals.mp4 (31.25 MB)
4 -Fast Performance with Categories.mp4 (15.65 MB)
5 -Categorical Methods.mp4 (36.39 MB)
6 -Dummy Variables for Modeling.mp4 (7.25 MB)
7 -Group Transforms and GroupBy.mp4 (38.87 MB)
8 -Resampling of Grouped Time.mp4 (36.61 MB)
9 -Method Chaining.mp4 (52.06 MB)
1 -Introduction.mp4 (12.33 MB)
10 -Estimating Time Series.mp4 (20.35 MB)
11 -Scikit-Learn.mp4 (29.84 MB)
12 -Scikit-Learn - 2.mp4 (61.57 MB)
2 -Pandas and Model Code.mp4 (32.14 MB)
3 -Pandas and Model Code - 2.mp4 (20.68 MB)
4 -Patsy.mp4 (19.06 MB)
5 -Patsy - 2.mp4 (20.99 MB)
6 -Data Transformations.mp4 (30.85 MB)
7 -Categorical Data.mp4 (38.55 MB)
8 -Estimating Linear Models.mp4 (30.66 MB)
9 -Estimating Linear Models - 2.mp4 (25.64 MB)
1 -USA gov Data.mp4 (27.45 MB)
10 -Analyzing Naming Trends.mp4 (25.42 MB)
11 -Increase in Naming Diversity.mp4 (32.43 MB)
12 -Increase in Naming Diversity - 2.mp4 (18.88 MB)
13 -Last Letter.mp4 (42.35 MB)
14 -Last Letter - 2.mp4 (22.95 MB)
15 -USDA Food Database.mp4 (22.65 MB)
16 -USDA Food Database - 2.mp4 (47.27 MB)
17 -USDA Food Database - 3.mp4 (52.75 MB)
18 -2012 Federal Election Commission Database.mp4 (60.8 MB)
19 -Donation Statistics by Occupation and Employer.mp4 (82.37 MB)
2 -Counting Time Zone in Python.mp4 (43.7 MB)
20 -Donation Amounts and by States.mp4 (38.32 MB)
3 -Counting Time Zone in Python - 2.mp4 (22.45 MB)
4 -Counting Time Zone in Python - 3.mp4 (67.85 MB)
5 -MovieLens 1M Dataset.mp4 (40.09 MB)
6 -MovieLens 1M Dataset - 2.mp4 (46.75 MB)
7 -Rating Disagreement.mp4 (27.34 MB)
8 -US Baby Names 1880-2010.mp4 (43.28 MB)
9 -US Baby Names 1880-2010 - 2.mp4 (48.98 MB)

]
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