Linkedin Introduction to Artificial Intelligence 2023
Seeders : 6 Leechers : 4
| Torrent Hash : | 5A8870B062CF26066E8422264FC8E61D35A2A04F |
| Torrent Added : | at Oct. 22, 2023, 9:47 a.m. in Other |
| Torrent Size : | 1.1 GB |
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Linkedin Introduction to Artificial Intelligence 2023
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Linkedin Introduction to Artificial Intelligence 2023
Get Bonus Downloads Here.url -
001. Why you need to know about artificial intelligence.en.srt -
001. Why you need to know about artificial intelligence.mp4 -
002. Define general intelligence.en.srt -
002. Define general intelligence.mp4 -
003. The general problem-solver.en.srt -
003. The general problem-solver.mp4 -
004. Strong vs. weak AI.en.srt -
004. Strong vs. weak AI.mp4 -
005. Machine learning.en.srt -
005. Machine learning.mp4 -
006. Artificial neural networks.en.srt -
006. Artificial neural networks.mp4 -
007. Searching for patterns in data.en.srt -
007. Searching for patterns in data.mp4 -
008. Robotics.en.srt -
008. Robotics.mp4 -
009. Natural language processing.en.srt -
009. Natural language processing.mp4 -
010. The Internet of Things.en.srt -
010. The Internet of Things.mp4 -
011. Labeled and unlabeled data.en.srt -
011. Labeled and unlabeled data.mp4 -
012. Massive datasets.en.srt -
012. Massive datasets.mp4 -
013. Classify data.en.srt -
013. Classify data.mp4 -
014. Cluster data.en.srt -
014. Cluster data.mp4 -
015. Reinforcement learning.en.srt -
015. Reinforcement learning.mp4 -
016. Common algorithms.en.srt -
016. Common algorithms.mp4 -
017. K-nearest neighbor.en.srt -
017. K-nearest neighbor.mp4 -
018. K-means clustering.en.srt -
018. K-means clustering.mp4 -
019. Regression.en.srt -
019. Regression.mp4 -
020. Naive Bayes.en.srt -
020. Naive Bayes.mp4 -
021. Select the best algorithm.en.srt -
021. Select the best algorithm.mp4 -
022. Follow the data.en.srt -
022. Follow the data.mp4 -
023. Overfitting and underfitting.en.srt -
023. Overfitting and underfitting.mp4 -
024. Build a neural network.en.srt -
024. Build a neural network.mp4 -
025. Weighing the connections.en.srt -
025. Weighing the connections.mp4 -
026. The activation bias.en.srt -
026. The activation bias.mp4 -
027. Learning from mistakes.en.srt -
027. Learning from mistakes.mp4 -
028. Step through the network.en.srt -
028. Step through the network.mp4 -
029. Using AI systems.en.srt -
029. Using AI systems.mp4 -
030. Applying AI to solve problems.en.srt -
030. Applying AI to solve problems.mp4 -
Bonus Resources.txt -
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Get Bonus Downloads Here.url -
178 bytes
001. Why you need to know about artificial intelligence.en.srt -
1.7 KB
001. Why you need to know about artificial intelligence.mp4 -
13.2 MB
002. Define general intelligence.en.srt -
5.5 KB
002. Define general intelligence.mp4 -
38.9 MB
003. The general problem-solver.en.srt -
5.6 KB
003. The general problem-solver.mp4 -
37.7 MB
004. Strong vs. weak AI.en.srt -
5.3 KB
004. Strong vs. weak AI.mp4 -
36.5 MB
005. Machine learning.en.srt -
5.7 KB
005. Machine learning.mp4 -
40.2 MB
006. Artificial neural networks.en.srt -
5.5 KB
006. Artificial neural networks.mp4 -
37.3 MB
007. Searching for patterns in data.en.srt -
6.1 KB
007. Searching for patterns in data.mp4 -
43.2 MB
008. Robotics.en.srt -
5.8 KB
008. Robotics.mp4 -
40.1 MB
009. Natural language processing.en.srt -
6.1 KB
009. Natural language processing.mp4 -
41.4 MB
010. The Internet of Things.en.srt -
5.7 KB
010. The Internet of Things.mp4 -
40.0 MB
011. Labeled and unlabeled data.en.srt -
5.6 KB
011. Labeled and unlabeled data.mp4 -
37.7 MB
012. Massive datasets.en.srt -
6.4 KB
012. Massive datasets.mp4 -
44.3 MB
013. Classify data.en.srt -
5.8 KB
013. Classify data.mp4 -
40.6 MB
014. Cluster data.en.srt -
6.1 KB
014. Cluster data.mp4 -
41.2 MB
015. Reinforcement learning.en.srt -
5.5 KB
015. Reinforcement learning.mp4 -
38.1 MB
016. Common algorithms.en.srt -
5.8 KB
016. Common algorithms.mp4 -
40.0 MB
017. K-nearest neighbor.en.srt -
5.8 KB
017. K-nearest neighbor.mp4 -
40.1 MB
018. K-means clustering.en.srt -
6.3 KB
018. K-means clustering.mp4 -
42.4 MB
019. Regression.en.srt -
6.1 KB
019. Regression.mp4 -
41.3 MB
020. Naive Bayes.en.srt -
5.7 KB
020. Naive Bayes.mp4 -
42.1 MB
021. Select the best algorithm.en.srt -
5.9 KB
021. Select the best algorithm.mp4 -
40.4 MB
022. Follow the data.en.srt -
5.2 KB
022. Follow the data.mp4 -
36.5 MB
023. Overfitting and underfitting.en.srt -
5.5 KB
023. Overfitting and underfitting.mp4 -
40.2 MB
024. Build a neural network.en.srt -
5.5 KB
024. Build a neural network.mp4 -
40.6 MB
025. Weighing the connections.en.srt -
5.3 KB
025. Weighing the connections.mp4 -
36.9 MB
026. The activation bias.en.srt -
5.3 KB
026. The activation bias.mp4 -
36.8 MB
027. Learning from mistakes.en.srt -
5.5 KB
027. Learning from mistakes.mp4 -
40.8 MB
028. Step through the network.en.srt -
6.3 KB
028. Step through the network.mp4 -
45.5 MB
029. Using AI systems.en.srt -
5.4 KB
029. Using AI systems.mp4 -
39.2 MB
030. Applying AI to solve problems.en.srt -
2.5 KB
030. Applying AI to solve problems.mp4 -
17.0 MB
Bonus Resources.txt -
386 bytes
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